{"id":"W4245596343","doi":"10.1515/iupac.73.0485","title":"Pa","year":2016,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Okanagan College","funders":"","keywords":"Table (database); Product (mathematics); Commission; Food science; Chemistry; Biochemistry; Organic chemistry; Polymer science; Computer science; Political science; Mathematics; Data mining; Law","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":[0.0008338701,0.001476709,0.001304611,0.003333132,0.0007480821,0.003990798,0.001906957,0.001477569,0.2691318],"category_scores_gemma":[0.008346448,0.0005885987,0.001125255,0.006074841,0.0003267714,0.002525417,0.002472316,0.00145915,0.4119836],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009844482,"about_ca_system_score_gemma":0.001998254,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01104094,"about_ca_topic_score_gemma":0.01409164,"domain_scores_codex":[0.9983873,0.0002514097,0.0001960933,0.0006757094,0.0002979207,0.0001914892],"domain_scores_gemma":[0.9975194,0.0005406271,0.0003061327,0.0006752788,0.000744178,0.0002143693],"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":[0.0001080394,0.00001571877,0.001732509,0.0009222836,0.00003398831,0.00002510078,0.00002841609,0.0001450018,0.000118252,0.001130196,0.9827551,0.01298536],"study_design_scores_gemma":[0.00005858609,0.000009846178,0.00227889,0.0004142081,0.00001672145,0.00006564955,0.00004432067,0.0001539132,0.0001471196,0.001249428,0.9955487,0.00001266864],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001423391,0.0001738962,0.0001881166,0.0001319002,0.00005157867,0.00001625199,0.9949326,0.0005454139,0.003817893],"genre_scores_gemma":[0.0005352915,0.0002182756,0.0003131966,0.0001465405,0.00002246014,0.00006106464,0.9958159,0.0001622837,0.002724922],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.7308682,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01684227673020045,"score_gpt":0.428358477889987,"score_spread":0.4115162011597865,"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."}}