{"id":"W4256727499","doi":"10.1515/iupac.88.1497","title":"Wharton’s Jelly","year":2017,"lang":"de","type":"dataset","venue":"IUPAC Standards Online","topic":"Effects and risks of endocrine disrupting chemicals","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canada Research Chairs; University of Toronto","funders":"","keywords":"Glossary; Terminology; Relation (database); Computer science; Linguistics; Philosophy; Data mining","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009933671,0.001131345,0.001193363,0.005917696,0.0007580857,0.00337842,0.001671844,0.001180673,0.2376188],"category_scores_gemma":[0.01334676,0.0005816175,0.001218786,0.01193177,0.0005116325,0.002782262,0.00247941,0.001578849,0.2338747],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001019472,"about_ca_system_score_gemma":0.002107438,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.017723,"about_ca_topic_score_gemma":0.02733273,"domain_scores_codex":[0.9988106,0.0002016998,0.0002855888,0.0003131359,0.0002745088,0.0001144596],"domain_scores_gemma":[0.9959399,0.001562175,0.0005528868,0.0007907255,0.0009351514,0.0002192218],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00004018488,0.000004779499,0.0005274381,0.001008826,0.00001780183,0.00001791477,0.00002582255,0.00007798695,0.00005084174,0.000741671,0.9908338,0.006652974],"study_design_scores_gemma":[0.00002548299,0.00000411006,0.001512394,0.0004749752,0.000008747181,0.00002978303,0.00005383165,0.00005059263,0.00004659513,0.0007532962,0.9970309,0.000009286166],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001099622,0.0002943521,0.0001530015,0.0001561086,0.0001001104,0.00002242547,0.9950871,0.0002439609,0.003833026],"genre_scores_gemma":[0.0006951808,0.0005700438,0.0005750813,0.000230323,0.00003826568,0.0001212259,0.9927086,0.0002063419,0.004854984],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.2376188,"threshold_uncertainty_score":0.7949141,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01324301827354519,"score_gpt":0.4560448178426921,"score_spread":0.4428017995691469,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}