{"id":"W6886025565","doi":"10.14288/1.0354837","title":"British Columbia : farms, fisheries, forests, mines","year":2017,"lang":"en","type":"article","venue":"Open Collections","topic":"Canadian Identity and History","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Settlement (finance); Orange (colour); Cover (algebra); Human settlement","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":[0.0001572414,0.0005527592,0.0002357291,0.001583827,0.005604142,0.00290574,0.0007549245,0.0008048536,0.1456442],"category_scores_gemma":[0.0005799168,0.0003869051,0.0001031612,0.007431932,0.0009817708,0.0009751572,0.001024009,0.001150324,0.01786901],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01632206,"about_ca_system_score_gemma":0.03242221,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.984116,"about_ca_topic_score_gemma":0.996186,"domain_scores_codex":[0.9998038,0.00001379801,0.000008313961,0.00002337711,0.00006672455,0.00008388367],"domain_scores_gemma":[0.9995859,0.00002327565,0.00002106686,0.00001202855,0.0002118005,0.0001459257],"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":[0.00001964046,0.00001150676,0.00269077,0.0002510046,0.000002637959,0.0001992731,0.0009605833,0.00009518368,0.0001714939,0.002308676,0.916454,0.07683507],"study_design_scores_gemma":[0.000006046353,0.000003882855,0.03981114,0.0004243075,0.000004300533,0.00007883258,0.004350278,0.00003905351,0.0000639902,0.0003557352,0.9548482,0.00001425693],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.02548724,0.03347747,0.0004760958,0.0159636,0.001586364,0.000140598,0.03715734,0.0003679913,0.8853433],"genre_scores_gemma":[0.06595116,0.01399442,0.000635091,0.001310629,0.0001007252,0.00007825457,0.0071066,0.0001048134,0.9107182],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.1456442,"threshold_uncertainty_score":0.4872284,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0232852798859414,"score_gpt":0.2565091407201563,"score_spread":0.2332238608342149,"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."}}