[BypassAS] prepare FOS subject, test and model for FOS and BipFinder scores

This commit is contained in:
Miriam Baglioni 2021-11-08 16:44:19 +01:00
parent 7bd224f051
commit a7d50c499b
11 changed files with 774 additions and 0 deletions

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package eu.dnetlib.dhp.bypassactionset;
import eu.dnetlib.dhp.application.ArgumentApplicationParser;
import eu.dnetlib.dhp.bypassactionset.model.FOSDataModel;
import org.apache.commons.io.IOUtils;
import org.apache.spark.SparkConf;
import org.apache.spark.api.java.function.FlatMapFunction;
import org.apache.spark.sql.Dataset;
import org.apache.spark.sql.Encoders;
import org.apache.spark.sql.SaveMode;
import org.apache.spark.sql.SparkSession;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
import java.io.Serializable;
import java.util.ArrayList;
import java.util.Arrays;
import java.util.List;
import static eu.dnetlib.dhp.PropagationConstant.*;
import static eu.dnetlib.dhp.common.SparkSessionSupport.runWithSparkSession;
public class DistributeFOSSparkJob implements Serializable {
private static final Logger log = LoggerFactory.getLogger(DistributeFOSSparkJob.class);
public static void main(String[] args) throws Exception {
String jsonConfiguration = IOUtils
.toString(
DistributeFOSSparkJob.class
.getResourceAsStream(
"/eu/dnetlib/dhp/bypassactionset/distribute_fos_parameters.json"));
final ArgumentApplicationParser parser = new ArgumentApplicationParser(jsonConfiguration);
parser.parseArgument(args);
Boolean isSparkSessionManaged = isSparkSessionManaged(parser);
log.info("isSparkSessionManaged: {}", isSparkSessionManaged);
String sourcePath = parser.get("sourcePath");
log.info("sourcePath: {}", sourcePath);
final String outputPath = parser.get("outputPath");
log.info("outputPath: {}", outputPath);
SparkConf conf = new SparkConf();
runWithSparkSession(
conf,
isSparkSessionManaged,
spark -> {
removeOutputDir(spark, outputPath);
distributeFOSdois(
spark,
sourcePath,
outputPath
);
});
}
private static void distributeFOSdois(SparkSession spark, String sourcePath, String outputPath) {
Dataset<FOSDataModel> fosDataset = readPath(spark, sourcePath, FOSDataModel.class);
fosDataset.flatMap((FlatMapFunction<FOSDataModel, FOSDataModel>) v -> {
List<FOSDataModel> fosList = new ArrayList<>();
final String level1 = v.getLevel1();
final String level2 = v.getLevel2();
final String level3 = v.getLevel3();
Arrays.stream(v.getDoi().split("\u0002")).forEach(d -> fosList.add(FOSDataModel.newInstance(d, level1, level2, level3)));
return fosList.iterator();
}, Encoders.bean(FOSDataModel.class))
.write()
.mode(SaveMode.Overwrite)
.option("compression","gzip")
.json(outputPath);
}
}

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package eu.dnetlib.dhp.bypassactionset;
import eu.dnetlib.dhp.application.ArgumentApplicationParser;
import eu.dnetlib.dhp.common.collection.GetCSV;
import org.apache.commons.io.IOUtils;
import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.FileSystem;
import org.apache.hadoop.fs.Path;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
import java.io.*;
import java.util.Objects;
import java.util.Optional;
public class GetFOSData implements Serializable {
private static final Logger log = LoggerFactory.getLogger(GetFOSData.class);
public static final char DEFAULT_DELIMITER = '\t';
public static void main(final String[] args) throws Exception {
final ArgumentApplicationParser parser = new ArgumentApplicationParser(
IOUtils
.toString(
Objects
.requireNonNull(
GetFOSData.class
.getResourceAsStream(
"/eu/dnetlib/dhp/bypassactionset/get_fos_parameters.json"))));
parser.parseArgument(args);
//the path where the original fos csv file is stored
final String inputPath = parser.get("inputPath");
log.info("inputPath {}", inputPath);
//the path where to put the file as json
final String outputFile = parser.get("outputFile");
log.info("outputFile {}", outputFile);
final String hdfsNameNode = parser.get("hdfsNameNode");
log.info("hdfsNameNode {}", hdfsNameNode);
final String classForName = parser.get("classForName");
log.info("classForName {}", classForName);
final char delimiter = Optional
.ofNullable(parser.get("delimiter"))
.map(s -> s.charAt(0))
.orElse(DEFAULT_DELIMITER);
log.info("delimiter {}", delimiter);
Configuration conf = new Configuration();
conf.set("fs.defaultFS", hdfsNameNode);
FileSystem fileSystem = FileSystem.get(conf);
new GetFOSData().doRewrite(inputPath, outputFile, classForName, delimiter, fileSystem);
}
public void doRewrite(String inputPath, String outputFile, String classForName, char delimiter, FileSystem fs)
throws IOException, ClassNotFoundException{
//reads the csv and writes it as its json equivalent
try (InputStreamReader reader = new InputStreamReader(fs.open(new Path (inputPath)))) {
GetCSV.getCsv(fs, reader, outputFile, classForName, delimiter);
}
}
}

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package eu.dnetlib.dhp.bypassactionset.model;
import java.io.Serializable;
import java.util.ArrayList;
import java.util.HashMap;
import java.util.List;
/**
* Class that maps the model of the bipFinder! input data.
* Only needed for deserialization purposes
*/
public class BipDeserialize extends HashMap<String, List<Score>> implements Serializable {
public BipDeserialize() {
super();
}
public List<Score> get(String key) {
if (super.get(key) == null) {
return new ArrayList<>();
}
return super.get(key);
}
}

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package eu.dnetlib.dhp.bypassactionset.model;
import com.opencsv.bean.CsvBindByPosition;
import java.io.Serializable;
public class FOSDataModel implements Serializable {
@CsvBindByPosition(position = 1)
// @CsvBindByName(column = "doi")
private String doi;
@CsvBindByPosition(position = 2)
// @CsvBindByName(column = "level1")
private String level1;
@CsvBindByPosition(position = 3)
// @CsvBindByName(column = "level2")
private String level2;
@CsvBindByPosition(position = 4)
// @CsvBindByName(column = "level3")
private String level3;
public FOSDataModel() {
}
public FOSDataModel(String doi, String level1, String level2, String level3) {
this.doi = doi;
this.level1 = level1;
this.level2 = level2;
this.level3 = level3;
}
public static FOSDataModel newInstance(String d, String level1, String level2, String level3) {
return new FOSDataModel(d, level1, level2, level3);
}
public String getDoi() {
return doi;
}
public void setDoi(String doi) {
this.doi = doi;
}
public String getLevel1() {
return level1;
}
public void setLevel1(String level1) {
this.level1 = level1;
}
public String getLevel2() {
return level2;
}
public void setLevel2(String level2) {
this.level2 = level2;
}
public String getLevel3() {
return level3;
}
public void setLevel3(String level3) {
this.level3 = level3;
}
}

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package eu.dnetlib.dhp.bypassactionset.model;
import java.io.Serializable;
public class KeyValue implements Serializable {
private String key;
private String value;
public String getKey() {
return key;
}
public void setKey(String key) {
this.key = key;
}
public String getValue() {
return value;
}
public void setValue(String value) {
this.value = value;
}
}

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package eu.dnetlib.dhp.bypassactionset.model;
import java.io.Serializable;
import java.util.List;
/**
* represents the score in the input file
*/
public class Score implements Serializable {
private String id;
private List<KeyValue> unit;
public String getId() {
return id;
}
public void setId(String id) {
this.id = id;
}
public List<KeyValue> getUnit() {
return unit;
}
public void setUnit(List<KeyValue> unit) {
this.unit = unit;
}
}

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[
{
"paramName":"s",
"paramLongName":"sourcePath",
"paramDescription": "the path of the sequencial file to read",
"paramRequired": true
},
{
"paramName":"out",
"paramLongName":"outputPath",
"paramDescription": "the output path",
"paramRequired": true
},
{
"paramName": "ssm",
"paramLongName": "isSparkSessionManaged",
"paramDescription": "true if the spark session is managed, false otherwise",
"paramRequired": false
}
]

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[
{
"paramName":"s",
"paramLongName":"sourcePath",
"paramDescription": "the path of the sequencial file to read",
"paramRequired": true
},
{
"paramName":"out",
"paramLongName":"outputPath",
"paramDescription": "the output path",
"paramRequired": true
},
{
"paramName": "ssm",
"paramLongName": "isSparkSessionManaged",
"paramDescription": "true if the spark session is managed, false otherwise",
"paramRequired": false
},
{
"paramName": "hnn",
"paramLongName": "hdfsNameNode",
"paramDescription": "the path used to store the HostedByMap",
"paramRequired": true
}
]

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package eu.dnetlib.dhp.bypassactionset;
import com.fasterxml.jackson.databind.ObjectMapper;
import eu.dnetlib.dhp.bypassactionset.model.FOSDataModel;
import eu.dnetlib.dhp.common.collection.CollectorException;
import eu.dnetlib.dhp.countrypropagation.CountryPropagationJobTest;
import org.apache.commons.io.FileUtils;
import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.FileSystem;
import org.apache.hadoop.fs.LocalFileSystem;
import java.nio.file.Path;
import org.apache.spark.SparkConf;
import org.apache.spark.api.java.JavaRDD;
import org.apache.spark.api.java.JavaSparkContext;
import org.apache.spark.sql.SparkSession;
import org.junit.jupiter.api.AfterAll;
import org.junit.jupiter.api.BeforeAll;
import org.junit.jupiter.api.Test;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
import java.io.BufferedReader;
import java.io.IOException;
import java.io.InputStreamReader;
import java.nio.file.Files;
import static org.junit.jupiter.api.Assertions.assertEquals;
import static org.junit.jupiter.api.Assertions.assertTrue;
public class GetFOSTest {
private static final Logger log = LoggerFactory.getLogger(GetFOSTest.class);
private static Path workingDir;
private static SparkSession spark;
private static LocalFileSystem fs;
private static final ObjectMapper OBJECT_MAPPER = new ObjectMapper();
@BeforeAll
public static void beforeAll() throws IOException {
workingDir = Files.createTempDirectory(CountryPropagationJobTest.class.getSimpleName());
fs = FileSystem.getLocal(new Configuration());
log.info("using work dir {}", workingDir);
SparkConf conf = new SparkConf();
conf.setAppName(GetFOSTest.class.getSimpleName());
conf.setMaster("local[*]");
conf.set("spark.driver.host", "localhost");
conf.set("hive.metastore.local", "true");
conf.set("spark.ui.enabled", "false");
conf.set("spark.sql.warehouse.dir", workingDir.toString());
conf.set("hive.metastore.warehouse.dir", workingDir.resolve("warehouse").toString());
spark = SparkSession
.builder()
.appName(CountryPropagationJobTest.class.getSimpleName())
.config(conf)
.getOrCreate();
}
@AfterAll
public static void afterAll() throws IOException {
FileUtils.deleteDirectory(workingDir.toFile());
spark.stop();
}
@Test
void getFOSFileTest() throws CollectorException, IOException, ClassNotFoundException {
final String sourcePath = getClass()
.getResource("/eu/dnetlib/dhp/bypassactionset/fos/h2020_fos_sbs.csv")
.getPath();
final String outputPath = workingDir.toString() + "/fos.json";
new GetFOSData()
.doRewrite(sourcePath, outputPath, "eu.dnetlib.dhp.bypassactionset.FOSDataModel", '\t',fs );
BufferedReader in = new BufferedReader(new InputStreamReader(fs.open(new org.apache.hadoop.fs.Path(outputPath))));
String line;
int count = 0;
while ((line = in.readLine()) != null) {
FOSDataModel fos = new ObjectMapper().readValue(line, FOSDataModel.class);
System.out.println(new ObjectMapper().writeValueAsString(fos));
count += 1;
}
assertEquals(38, count);
}
@Test
void distributeDoiTest() throws Exception{
final String sourcePath = getClass()
.getResource("/eu/dnetlib/dhp/bypassactionset/fos/fos.json")
.getPath();
DistributeFOSSparkJob
.main(
new String[] {
"--isSparkSessionManaged", Boolean.FALSE.toString(),
"--sourcePath", sourcePath,
"-outputPath", workingDir.toString() + "/distribute"
});
final JavaSparkContext sc = JavaSparkContext.fromSparkContext(spark.sparkContext());
JavaRDD<FOSDataModel> tmp = sc
.textFile(workingDir.toString() + "/distribute")
.map(item -> OBJECT_MAPPER.readValue(item, FOSDataModel.class));
assertEquals(50, tmp.count());
assertEquals(1, tmp.filter(row -> row.getDoi().equals("10.3390/s18072310")).count());
assertEquals("engineering and technology", tmp.filter(r -> r.getDoi().equals("10.3390/s18072310")).collect().get(0).getLevel1());
assertEquals("nano-technology", tmp.filter(r -> r.getDoi().equals("10.3390/s18072310")).collect().get(0).getLevel2());
assertEquals("nanoscience & nanotechnology", tmp.filter(r -> r.getDoi().equals("10.3390/s18072310")).collect().get(0).getLevel3());
assertEquals(1, tmp.filter(row -> row.getDoi().equals("10.1111/1365-2656.12831")).count());
assertEquals("social sciences", tmp.filter(r -> r.getDoi().equals("10.1111/1365-2656.12831")).collect().get(0).getLevel1());
assertEquals("psychology and cognitive sciences", tmp.filter(r -> r.getDoi().equals("10.1111/1365-2656.12831")).collect().get(0).getLevel2());
assertEquals("NULL", tmp.filter(r -> r.getDoi().equals("10.1111/1365-2656.12831")).collect().get(0).getLevel3());
// {"doi":"10.1111/1365-2656.12831\u000210.17863/cam.24369","level1":"social sciences","level2":"psychology and cognitive sciences","level3":"NULL"}
}
/**
* @Test
* void testCountryPropagationSoftware() throws Exception {
* final String sourcePath = getClass()
* .getResource("/eu/dnetlib/dhp/countrypropagation/sample/software")
* .getPath();
* final String preparedInfoPath = getClass()
* .getResource("/eu/dnetlib/dhp/countrypropagation/preparedInfo")
* .getPath();
* SparkCountryPropagationJob
* .main(
* new String[] {
* "--isSparkSessionManaged", Boolean.FALSE.toString(),
* "--sourcePath", sourcePath,
* "-saveGraph", "true",
* "-resultTableName", Software.class.getCanonicalName(),
* "-outputPath", workingDir.toString() + "/software",
* "-preparedInfoPath", preparedInfoPath
* });
*
* final JavaSparkContext sc = JavaSparkContext.fromSparkContext(spark.sparkContext());
*
* JavaRDD<Software> tmp = sc
* .textFile(workingDir.toString() + "/software")
* .map(item -> OBJECT_MAPPER.readValue(item, Software.class));
*
* // tmp.map(s -> new Gson().toJson(s)).foreach(s -> System.out.println(s));
*
* Assertions.assertEquals(10, tmp.count());
*
* Dataset<Software> verificationDs = spark.createDataset(tmp.rdd(), Encoders.bean(Software.class));
*
* Assertions.assertEquals(6, verificationDs.filter("size(country) > 0").count());
* Assertions.assertEquals(3, verificationDs.filter("size(country) = 1").count());
* Assertions.assertEquals(3, verificationDs.filter("size(country) = 2").count());
* Assertions.assertEquals(0, verificationDs.filter("size(country) > 2").count());
*
* Dataset<String> countryExploded = verificationDs
* .flatMap(
* (FlatMapFunction<Software, Country>) row -> row.getCountry().iterator(), Encoders.bean(Country.class))
* .map((MapFunction<Country, String>) Qualifier::getClassid, Encoders.STRING());
*
* Assertions.assertEquals(9, countryExploded.count());
*
* Assertions.assertEquals(1, countryExploded.filter("value = 'FR'").count());
* Assertions.assertEquals(1, countryExploded.filter("value = 'TR'").count());
* Assertions.assertEquals(2, countryExploded.filter("value = 'IT'").count());
* Assertions.assertEquals(1, countryExploded.filter("value = 'US'").count());
* Assertions.assertEquals(1, countryExploded.filter("value = 'MX'").count());
* Assertions.assertEquals(1, countryExploded.filter("value = 'CH'").count());
* Assertions.assertEquals(2, countryExploded.filter("value = 'JP'").count());
*
* Dataset<Tuple2<String, String>> countryExplodedWithCountryclassid = verificationDs
* .flatMap((FlatMapFunction<Software, Tuple2<String, String>>) row -> {
* List<Tuple2<String, String>> prova = new ArrayList<>();
* List<Country> countryList = row.getCountry();
* countryList
* .forEach(
* c -> prova
* .add(
* new Tuple2<>(
* row.getId(), c.getClassid())));
* return prova.iterator();
* }, Encoders.tuple(Encoders.STRING(), Encoders.STRING()));
*
* Assertions.assertEquals(9, countryExplodedWithCountryclassid.count());
*
* countryExplodedWithCountryclassid.show(false);
* Assertions
* .assertEquals(
* 1,
* countryExplodedWithCountryclassid
* .filter(
* "_1 = '50|od______1582::6e7a9b21a2feef45673890432af34244' and _2 = 'FR' ")
* .count());
* Assertions
* .assertEquals(
* 1,
* countryExplodedWithCountryclassid
* .filter(
* "_1 = '50|dedup_wf_001::40ea2f24181f6ae77b866ebcbffba523' and _2 = 'TR' ")
* .count());
* Assertions
* .assertEquals(
* 2,
* countryExplodedWithCountryclassid
* .filter(
* "_1 = '50|od______1106::2b7ca9726230be8e862be224fd463ac4' and (_2 = 'IT' or _2 = 'MX') ")
* .count());
* Assertions
* .assertEquals(
* 2,
* countryExplodedWithCountryclassid
* .filter(
* "_1 = '50|od_______935::46a0ad9964171c3dd13373f5427b9a1c' and (_2 = 'IT' or _2 = 'US') ")
* .count());
* Assertions
* .assertEquals(
* 1,
* countryExplodedWithCountryclassid
* .filter(
* "_1 = '50|dedup_wf_001::b67bc915603fc01e445f2b5888ba7218' and _2 = 'JP'")
* .count());
* Assertions
* .assertEquals(
* 2,
* countryExplodedWithCountryclassid
* .filter(
* "_1 = '50|od_______109::f375befa62a741e9250e55bcfa88f9a6' and (_2 = 'CH' or _2 = 'JP') ")
* .count());
*
* Dataset<Tuple2<String, String>> countryExplodedWithCountryclassname = verificationDs
* .flatMap(
* (FlatMapFunction<Software, Tuple2<String, String>>) row -> {
* List<Tuple2<String, String>> prova = new ArrayList<>();
* List<Country> countryList = row.getCountry();
* countryList
* .forEach(
* c -> prova
* .add(
* new Tuple2<>(
* row.getId(),
* c.getClassname())));
* return prova.iterator();
* },
* Encoders.tuple(Encoders.STRING(), Encoders.STRING()));
*
* countryExplodedWithCountryclassname.show(false);
* Assertions
* .assertEquals(
* 1,
* countryExplodedWithCountryclassname
* .filter(
* "_1 = '50|od______1582::6e7a9b21a2feef45673890432af34244' and _2 = 'France' ")
* .count());
* Assertions
* .assertEquals(
* 1,
* countryExplodedWithCountryclassname
* .filter(
* "_1 = '50|dedup_wf_001::40ea2f24181f6ae77b866ebcbffba523' and _2 = 'Turkey' ")
* .count());
* Assertions
* .assertEquals(
* 2,
* countryExplodedWithCountryclassname
* .filter(
* "_1 = '50|od______1106::2b7ca9726230be8e862be224fd463ac4' and (_2 = 'Italy' or _2 = 'Mexico') ")
* .count());
* Assertions
* .assertEquals(
* 2,
* countryExplodedWithCountryclassname
* .filter(
* "_1 = '50|od_______935::46a0ad9964171c3dd13373f5427b9a1c' and (_2 = 'Italy' or _2 = 'United States') ")
* .count());
* Assertions
* .assertEquals(
* 1,
* countryExplodedWithCountryclassname
* .filter(
* "_1 = '50|dedup_wf_001::b67bc915603fc01e445f2b5888ba7218' and _2 = 'Japan' ")
* .count());
* Assertions
* .assertEquals(
* 2,
* countryExplodedWithCountryclassname
* .filter(
* "_1 = '50|od_______109::f375befa62a741e9250e55bcfa88f9a6' and (_2 = 'Switzerland' or _2 = 'Japan') ")
* .count());
*
* Dataset<Tuple2<String, String>> countryExplodedWithCountryProvenance = verificationDs
* .flatMap(
* (FlatMapFunction<Software, Tuple2<String, String>>) row -> {
* List<Tuple2<String, String>> prova = new ArrayList<>();
* List<Country> countryList = row.getCountry();
* countryList
* .forEach(
* c -> prova
* .add(
* new Tuple2<>(
* row.getId(),
* c
* .getDataInfo()
* .getInferenceprovenance())));
* return prova.iterator();
* },
* Encoders.tuple(Encoders.STRING(), Encoders.STRING()));
*
* Assertions
* .assertEquals(
* 7, countryExplodedWithCountryProvenance.filter("_2 = 'propagation'").count());
* }
*/
}

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{"doi":"10.3390/s18072310","level1":"engineering and technology","level2":"nano-technology","level3":"nanoscience & nanotechnology"}
{"doi":"10.1111/1365-2656.12831\u000210.17863/cam.24369","level1":"social sciences","level2":"psychology and cognitive sciences","level3":"NULL"}
{"doi":"10.3929/ethz-b-000187584\u000210.1002/chem.201701644","level1":"natural sciences","level2":"NULL","level3":"NULL"}
{"doi":"10.1080/01913123.2017.1367361","level1":"medical and health sciences","level2":"clinical medicine","level3":"oncology & carcinogenesis"}
{"doi":"10.1051/e3sconf/20199207011","level1":"natural sciences","level2":"earth and related environmental sciences","level3":"environmental sciences"}
{"doi":"10.1038/onc.2015.333","level1":"medical and health sciences","level2":"clinical medicine","level3":"oncology & carcinogenesis"}
{"doi":"10.1093/mnras/staa256","level1":"natural sciences","level2":"physical sciences","level3":"NULL"}
{"doi":"10.1016/j.jclepro.2018.07.166","level1":"engineering and technology","level2":"other engineering and technologies","level3":"building & construction"}
{"doi":"10.1103/physrevlett.125.037403","level1":"natural sciences","level2":"physical sciences","level3":"nuclear & particles physics"}
{"doi":"10.1080/03602532.2017.1316285","level1":"natural sciences","level2":"NULL","level3":"NULL"}
{"doi":"10.1001/jamanetworkopen.2019.1868","level1":"medical and health sciences","level2":"other medical science","level3":"health policy & services"}
{"doi":"10.1128/mra.00874-18","level1":"natural sciences","level2":"biological sciences","level3":"plant biology & botany"}
{"doi":"10.1016/j.nancom.2018.03.001","level1":"engineering and technology","level2":"NULL","level3":"NULL"}
{"doi":"10.1112/topo.12174","level1":"natural sciences","level2":"NULL","level3":"NULL"}
{"doi":"10.12688/wellcomeopenres.15846.1","level1":"medical and health sciences","level2":"health sciences","level3":"NULL"}
{"doi":"10.21468/scipostphys.3.1.001","level1":"natural sciences","level2":"physical sciences","level3":"NULL"}
{"doi":"10.1088/1741-4326/ab6c77","level1":"natural sciences","level2":"physical sciences","level3":"nuclear & particles physics"}
{"doi":"10.1109/tpwrs.2019.2944747","level1":"engineering and technology","level2":"electrical engineering, electronic engineering, information engineering","level3":"electrical & electronic engineering"}
{"doi":"10.1016/j.expthermflusci.2019.109994\u000210.17863/cam.46212","level1":"engineering and technology","level2":"mechanical engineering","level3":"mechanical engineering & transports"}
{"doi":"10.1109/tc.2018.2860012","level1":"engineering and technology","level2":"electrical engineering, electronic engineering, information engineering","level3":"computer hardware & architecture"}
{"doi":"10.1002/mma.6622","level1":"natural sciences","level2":"mathematics","level3":"numerical & computational mathematics"}
{"doi":"10.1051/radiopro/2020020","level1":"natural sciences","level2":"chemical sciences","level3":"NULL"}
{"doi":"10.1007/s12268-019-1003-4","level1":"medical and health sciences","level2":"basic medicine","level3":"NULL"}
{"doi":"10.3390/cancers12010236","level1":"medical and health sciences","level2":"health sciences","level3":"biochemistry & molecular biology"}
{"doi":"10.6084/m9.figshare.9912614\u000210.6084/m9.figshare.9912614.v1\u000210.1080/00268976.2019.1665199","level1":"natural sciences","level2":"chemical sciences","level3":"physical chemistry"}
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