{"id":"W4243125888","doi":"10.1515/iupac.88.0872","title":"Grey Matter","year":2017,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"Air Quality Monitoring and Forecasting","field":"Environmental Science","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":[0.001826211,0.001412389,0.002853568,0.009726915,0.001350448,0.007559538,0.003063577,0.003170009,0.5706086],"category_scores_gemma":[0.03072041,0.0008194576,0.002045699,0.02112575,0.0009494034,0.005041727,0.004113997,0.002296496,0.4126452],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002257213,"about_ca_system_score_gemma":0.007609095,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01264389,"about_ca_topic_score_gemma":0.01791204,"domain_scores_codex":[0.996896,0.0005109558,0.0006992589,0.0008469882,0.0006924707,0.0003543405],"domain_scores_gemma":[0.9891158,0.004285255,0.001523212,0.001606561,0.002702447,0.0007667477],"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":[0.00003951628,0.000004898388,0.0002295861,0.004120015,0.00002600163,0.00002725585,0.00003896992,0.00005550534,0.00004965901,0.001501793,0.9849107,0.008996241],"study_design_scores_gemma":[0.00003626319,0.000002538976,0.0005696965,0.001838422,0.00001376856,0.00002816318,0.00003861717,0.00002655185,0.00003273255,0.001815931,0.9955869,0.00001051547],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00007636247,0.001007751,0.0001623501,0.0008229077,0.0003353521,0.00006090969,0.9848453,0.0003071315,0.01238194],"genre_scores_gemma":[0.0009487334,0.002537145,0.001170437,0.001302197,0.0002460783,0.0004173824,0.9842349,0.0003970466,0.008746125],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.5706086,"threshold_uncertainty_score":0.6124747,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02521617823231041,"score_gpt":0.4125023845337802,"score_spread":0.3872862063014698,"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."}}