{"id":"W4248421096","doi":"10.1515/iupac.73.0175","title":"Copra","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); Food science; Commission; 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":[],"consensus_categories":[],"category_scores_codex":[0.001651939,0.002467546,0.001928849,0.005524175,0.001350061,0.004584569,0.004026165,0.002647354,0.1166088],"category_scores_gemma":[0.01336338,0.0008322892,0.002154422,0.009431473,0.0005582118,0.003197681,0.003374853,0.002228357,0.2057796],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001608042,"about_ca_system_score_gemma":0.00393076,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01665078,"about_ca_topic_score_gemma":0.03049744,"domain_scores_codex":[0.9971679,0.0005356298,0.0003683556,0.001038563,0.00053178,0.0003577543],"domain_scores_gemma":[0.995742,0.001133882,0.000451931,0.001217252,0.001096924,0.0003579425],"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":[0.0001057597,0.00002025252,0.001140457,0.001370028,0.00005465288,0.00003191104,0.00003223013,0.000320289,0.0001240568,0.001000945,0.9908608,0.004938592],"study_design_scores_gemma":[0.0001228458,0.00001668133,0.002152735,0.0005090527,0.0000357194,0.00007232479,0.00006066198,0.0003458003,0.0002210011,0.001864155,0.9945734,0.00002568683],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001167519,0.0002014118,0.0001626279,0.0001198753,0.00004646352,0.00001691224,0.9973987,0.000584465,0.001352719],"genre_scores_gemma":[0.0002865635,0.0001497832,0.0003823267,0.00009171373,0.00001184339,0.00006525613,0.9981501,0.0001349142,0.000727559],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1166088,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01707529772577285,"score_gpt":0.4314269130741633,"score_spread":0.4143516153483904,"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."}}