{"id":"W4246659286","doi":"10.1515/iupac.88.0538","title":"Blastocoel","year":2017,"lang":"en","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":[0.001144896,0.001459259,0.001390223,0.003174402,0.0009665962,0.002292512,0.002559144,0.001614928,0.1212366],"category_scores_gemma":[0.006837578,0.000687078,0.001438867,0.004444992,0.0003980201,0.001629823,0.002058952,0.001718226,0.1235699],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001044121,"about_ca_system_score_gemma":0.00227207,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01224322,"about_ca_topic_score_gemma":0.02875667,"domain_scores_codex":[0.998903,0.0001783662,0.0001869014,0.0003496064,0.000248123,0.0001338998],"domain_scores_gemma":[0.9972723,0.0009055685,0.0003388868,0.0007502316,0.0005455496,0.0001873555],"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":[0.0002166763,0.00003260459,0.002649783,0.002165396,0.00005449774,0.00006030158,0.00003789383,0.0003452963,0.0003947679,0.001044016,0.9817709,0.01122776],"study_design_scores_gemma":[0.0001388541,0.00002272401,0.004562325,0.0005398507,0.00003300568,0.0000888244,0.00005274681,0.0001951659,0.0003952662,0.001258981,0.9926863,0.00002594352],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0002078763,0.0001747373,0.0001733736,0.00006061159,0.00003571752,0.00002590466,0.9971078,0.0004930759,0.001720896],"genre_scores_gemma":[0.0005798668,0.0002029627,0.0006342424,0.0001292247,0.000008783719,0.0001451285,0.9966239,0.0001285047,0.001547496],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1212366,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01162856834590813,"score_gpt":0.4608992042171819,"score_spread":0.4492706358712738,"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."}}