{"id":"W6964008608","doi":"10.25318/3410001601-fra","title":"Dépenses en immobilisations et réparations, extraction minière et extraction de pétrole et de gaz","year":2019,"lang":"fr","type":"dataset","venue":"Statistics Canada Dissemination","topic":"Robotics and Automated Systems","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Extraction (chemistry); Solvent extraction; Accelerated solvent extraction","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":[0.0008884984,0.003002455,0.001467258,0.00521966,0.001130327,0.001780005,0.002339131,0.002170875,0.01605809],"category_scores_gemma":[0.004770488,0.0005975387,0.002080969,0.006557881,0.000679563,0.001658931,0.001137044,0.001634151,0.02489251],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003116998,"about_ca_system_score_gemma":0.004619329,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.2208083,"about_ca_topic_score_gemma":0.4301849,"domain_scores_codex":[0.9987129,0.00008609795,0.0001754003,0.0003514148,0.0004421382,0.0002320786],"domain_scores_gemma":[0.9979817,0.0004388379,0.00024753,0.0002898126,0.0008892834,0.0001527859],"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":[0.0002097645,0.00004852226,0.006067445,0.001351221,0.00007980401,0.00004572918,0.00004415445,0.0007622853,0.0003180798,0.0003548095,0.9832852,0.007432833],"study_design_scores_gemma":[0.000309991,0.00005582945,0.05552979,0.0006775038,0.0001258569,0.0002286112,0.0003858366,0.001427167,0.001513043,0.001303189,0.9383529,0.00009029525],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.001002605,0.0003401164,0.00008078753,0.00007057207,0.00004198715,0.0000149132,0.9972668,0.0002064883,0.00097566],"genre_scores_gemma":[0.001603232,0.000221956,0.0003678645,0.00004082074,0.00001303388,0.00003752415,0.9962317,0.00003269115,0.001451012],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.7791917,"threshold_uncertainty_score":0.4390461,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01024578403350624,"score_gpt":0.3121784664889285,"score_spread":0.3019326824554223,"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."}}