{"id":"W4365149522","doi":"10.1515/iupac.94.0684","title":"Mu","year":2023,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"History and advancements in chemistry","field":"Chemistry","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Glossary; Terminology; Meaning (existential); Abandonment (legal); Field (mathematics); Computer science; Epistemology; Linguistics; Philosophy; Mathematics; Political science","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":[0.0008863219,0.002209278,0.00131804,0.003325643,0.00114805,0.003191885,0.002463203,0.001637088,0.2908372],"category_scores_gemma":[0.005634092,0.0006119725,0.001310977,0.004448766,0.0003672701,0.002790261,0.002748465,0.001597301,0.4454354],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001171969,"about_ca_system_score_gemma":0.001545505,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01469881,"about_ca_topic_score_gemma":0.03241383,"domain_scores_codex":[0.99873,0.0002109316,0.0001471618,0.0004771922,0.0002495276,0.0001851886],"domain_scores_gemma":[0.9979578,0.0004264115,0.0001633064,0.0007594599,0.0005169915,0.0001759255],"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":[0.0000537562,0.0000119825,0.0004017585,0.0003738043,0.00001347411,0.00001400947,0.00001737415,0.00006568032,0.0001117214,0.0004833633,0.9933355,0.00511755],"study_design_scores_gemma":[0.00006210953,0.0000134415,0.001755496,0.0002199303,0.00001268792,0.00005234219,0.00005584128,0.0001648213,0.000216399,0.001402217,0.9960246,0.00002014287],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001206952,0.0001204835,0.000152098,0.0001024826,0.00006899274,0.00001891783,0.9950954,0.0008940151,0.003426945],"genre_scores_gemma":[0.0002802753,0.00008448007,0.0003158224,0.0001381645,0.0000163997,0.00006459348,0.996681,0.0001675745,0.002251626],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.2908372,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01838053290362312,"score_gpt":0.4102934363098752,"score_spread":0.3919129034062521,"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."}}