{"id":"W2791287370","doi":"10.4095/287266","title":"Geochemistry database for carbonaceous and sulphidic metasediment horizons of the western Neoarchean Kidd-Munro Assemblage, Abitibi Subprovince, Ontario","year":2010,"lang":"en","type":"report","venue":"","topic":"Geochemistry and Geologic Mapping","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Natural Resources Canada","funders":"","keywords":"Assemblage (archaeology); Geochemistry; Geology; Paleontology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.0002733021,0.0006714705,0.0006555492,0.005614715,0.001512363,0.0008396172,0.001057601,0.0003009401,0.00745175],"category_scores_gemma":[0.0007244287,0.0003569096,0.0003269179,0.009956097,0.0002837294,0.0004321494,0.0007271057,0.0002702003,0.003455375],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.006152202,"about_ca_system_score_gemma":0.01214876,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9365352,"about_ca_topic_score_gemma":0.9707274,"domain_scores_codex":[0.999726,0.000004859037,0.00002181519,0.00005766826,0.0001366471,0.00005291322],"domain_scores_gemma":[0.9990576,0.00003192053,0.0001337589,0.000114671,0.0005523086,0.0001098115],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0009974252,0.0001396312,0.4068996,0.003020719,0.0004118081,0.0007942291,0.004423975,0.006242841,0.04349843,0.00447403,0.376922,0.1521753],"study_design_scores_gemma":[0.00009689187,0.00002499644,0.5125671,0.00009700152,0.0001167986,0.0001565962,0.0008738226,0.002151132,0.007714671,0.0004285859,0.4757304,0.00004185325],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.06277915,0.0006103298,0.002037618,0.00008626945,0.00001154979,0.0001195954,0.9157747,0.001164502,0.01741627],"genre_scores_gemma":[0.1263744,0.001250478,0.006624726,0.00004727155,0.00001270164,0.0002212899,0.8498801,0.0002007424,0.01538834],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.06346476,"threshold_uncertainty_score":0.127677,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02952231445981634,"score_gpt":0.2644895154562028,"score_spread":0.2349672009963865,"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."}}