{"id":"W4232177463","doi":"10.1515/iupac.73.0196","title":"Density","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; Law; 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":[0.001252143,0.002426922,0.00155482,0.005096449,0.001154899,0.003983405,0.003562919,0.002731446,0.1028281],"category_scores_gemma":[0.01438733,0.0007072301,0.00211504,0.00789582,0.0006019329,0.003413172,0.002601793,0.002424843,0.1536615],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001864557,"about_ca_system_score_gemma":0.002985536,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03225829,"about_ca_topic_score_gemma":0.04985444,"domain_scores_codex":[0.9976608,0.0003535645,0.0002730871,0.0009317364,0.0004563178,0.0003245502],"domain_scores_gemma":[0.9965736,0.001116239,0.0002813165,0.0007482977,0.001069897,0.0002106899],"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":[0.00009451724,0.00003187951,0.002750853,0.0009877122,0.00005446356,0.00003789181,0.00003480834,0.0004532626,0.00009750498,0.001077356,0.9865672,0.007812613],"study_design_scores_gemma":[0.0002106858,0.00003155566,0.00564459,0.0007880949,0.00006903752,0.0001989482,0.0001690727,0.001336299,0.0004446933,0.005198115,0.9858595,0.00004943719],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0002512301,0.0002346486,0.0002142838,0.0001443014,0.00005871611,0.00002289474,0.9973081,0.0004444338,0.001321413],"genre_scores_gemma":[0.0008350916,0.0001767293,0.0005487366,0.00009952482,0.00001917507,0.00009983586,0.9971285,0.00006721706,0.001025214],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8971719,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01655455473873397,"score_gpt":0.4153555882406885,"score_spread":0.3988010335019545,"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."}}