{"id":"W6964407992","doi":"10.25625/rzz9vm/fd9iwp","title":"2022-12-RZZ9VM_CANADIAN_SHIELD_MESOZOIC.csv","year":2022,"lang":"en","type":"dataset","venue":"Göttingen Research Online","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Process (computing); Identification (biology); Product (mathematics)","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006605879,0.001730409,0.00151043,0.004094812,0.001381692,0.003522804,0.00277487,0.001632754,0.2441191],"category_scores_gemma":[0.004921661,0.0009062181,0.0009057468,0.01062217,0.0004773897,0.001405677,0.002253295,0.001594428,0.2209315],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003755365,"about_ca_system_score_gemma":0.006750739,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.4117655,"about_ca_topic_score_gemma":0.5626601,"domain_scores_codex":[0.9993148,0.00006717582,0.00004050199,0.0001967971,0.0001652647,0.0002155417],"domain_scores_gemma":[0.9979673,0.0003550655,0.0001461056,0.0004385278,0.0007501525,0.0003427742],"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":[0.00001863127,0.000002957824,0.0002096482,0.0001685719,0.000007812631,0.000005483578,0.00001078575,0.00007925788,0.00002557011,0.0003633445,0.9984065,0.0007015487],"study_design_scores_gemma":[0.0001019844,0.000003453248,0.002167733,0.0001727083,0.000009887085,0.00001010881,0.00006229677,0.0001202015,0.0001003968,0.0005588615,0.9966757,0.00001664004],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00002685986,0.00002890166,0.00001364685,0.00003959154,0.0000122217,0.000002770053,0.9987659,0.0001347512,0.0009753563],"genre_scores_gemma":[0.000279859,0.00005371699,0.0001053084,0.00004276504,0.00000625415,0.00002678159,0.9972841,0.0001292061,0.002071947],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.5882345,"threshold_uncertainty_score":0.8187374,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1602061572680393,"score_gpt":0.4467907645017901,"score_spread":0.2865846072337508,"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."}}