{"id":"W4241288894","doi":"10.1515/iupac.88.1291","title":"Retinoic Acid","year":2017,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"Retinoids in leukemia and cellular processes","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canada Research Chairs; University of Toronto","funders":"","keywords":"Glossary; Terminology; Computer science; Linguistics; 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":[0.001242586,0.001357118,0.001595194,0.003941384,0.000798165,0.002519646,0.001925156,0.001452963,0.08101088],"category_scores_gemma":[0.007373489,0.0006531852,0.00165893,0.006830502,0.0003680268,0.001636621,0.002001587,0.001727406,0.08297924],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001221838,"about_ca_system_score_gemma":0.002700724,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01409555,"about_ca_topic_score_gemma":0.02865505,"domain_scores_codex":[0.9983248,0.0003152846,0.0004017064,0.0004795851,0.0003412614,0.0001372913],"domain_scores_gemma":[0.9970179,0.0009573908,0.0005004919,0.0007563526,0.0006094992,0.0001584017],"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":[0.0003424799,0.00003288131,0.002664701,0.006944609,0.0001401181,0.00006666602,0.0000794009,0.0004542321,0.0008990558,0.001685322,0.9593411,0.02734942],"study_design_scores_gemma":[0.0001117259,0.00001768827,0.003476474,0.001017633,0.00006122875,0.00008984513,0.0000470689,0.00009481838,0.0003429679,0.0007962142,0.9939224,0.0000219618],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0002043019,0.0006820953,0.00021404,0.00008786889,0.00004270475,0.00003162924,0.9962769,0.0002794401,0.002181019],"genre_scores_gemma":[0.000605136,0.0006669822,0.0007151386,0.0001574551,0.00001148845,0.0001408572,0.9961872,0.00007204592,0.00144378],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.08101088,"threshold_uncertainty_score":0.2710084,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01067495804902471,"score_gpt":0.3909210677891168,"score_spread":0.3802461097400922,"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."}}