{"id":"W4235768926","doi":"10.1515/iupac.88.0631","title":"Conceptus","year":2017,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canada Research Chairs; University of Toronto","funders":"","keywords":"Glossary; Terminology; Conceptus; Relation (database); Computer science; Biology; Linguistics; Pregnancy; Genetics; Fetus; Data mining; Philosophy","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":[0.0041131,0.001899251,0.001808419,0.009708448,0.001837685,0.006187754,0.003463591,0.002135341,0.2457046],"category_scores_gemma":[0.03535962,0.001114362,0.002122283,0.01495746,0.001032934,0.006548686,0.005048067,0.003295217,0.1967971],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003368709,"about_ca_system_score_gemma":0.007656801,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01515136,"about_ca_topic_score_gemma":0.01907133,"domain_scores_codex":[0.9949318,0.0010944,0.001360232,0.001095923,0.001055727,0.0004619135],"domain_scores_gemma":[0.9852072,0.00594944,0.001410475,0.002651894,0.00404585,0.0007350141],"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":[0.00006905664,0.00001112103,0.0005049055,0.001841403,0.00001777643,0.00001832098,0.0000786118,0.00009367685,0.00006031723,0.003301332,0.9853091,0.008694412],"study_design_scores_gemma":[0.000055382,0.000006808884,0.0007762953,0.0009274841,0.00001044803,0.00003377797,0.0001195956,0.00005870355,0.00005551859,0.002630115,0.9953098,0.00001609191],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001279724,0.0002875899,0.000363584,0.0002922169,0.0001507832,0.0001372289,0.9931018,0.0003895265,0.005149302],"genre_scores_gemma":[0.0005704167,0.0004403414,0.001633572,0.0003883038,0.00005510226,0.0010004,0.9925516,0.0003440323,0.003016348],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.2457046,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02725293789094348,"score_gpt":0.4744362048462961,"score_spread":0.4471832669553526,"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."}}