{"id":"W4249101259","doi":"10.1515/iupac.88.0948","title":"Iniopagus","year":2017,"lang":"sv","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":"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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0006977055,0.001310279,0.001330804,0.004386512,0.001167818,0.003786477,0.001406766,0.00101386,0.1815436],"category_scores_gemma":[0.005027744,0.0005651286,0.0009882997,0.007159235,0.0004324664,0.002558011,0.002875594,0.001662223,0.1876296],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008866878,"about_ca_system_score_gemma":0.00187764,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01345142,"about_ca_topic_score_gemma":0.01826209,"domain_scores_codex":[0.9989828,0.0001601496,0.0001665564,0.0003362808,0.0002325302,0.0001215274],"domain_scores_gemma":[0.9984434,0.0005154239,0.0002431298,0.0003699682,0.0003109846,0.0001170437],"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":[0.0001651511,0.00001939922,0.002696931,0.002463692,0.00004779616,0.00006097652,0.0001234185,0.0002148921,0.0003566367,0.002987479,0.96258,0.02828357],"study_design_scores_gemma":[0.00002341,0.000005080964,0.002407793,0.0003289267,0.00001349865,0.00003817398,0.00005550374,0.00005987727,0.00009313538,0.0008518238,0.9961134,0.000009365524],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.000472728,0.0004861984,0.0002506115,0.0001703663,0.0001127244,0.00002270227,0.9884752,0.0007221097,0.009287236],"genre_scores_gemma":[0.001181547,0.0005613921,0.0007027979,0.0002129506,0.00003587507,0.00008547818,0.9923052,0.0002880114,0.00462675],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8184564,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02063147924367471,"score_gpt":0.4361412054718034,"score_spread":0.4155097262281287,"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."}}