{"id":"W2791846511","doi":"10.4095/286029","title":"Séries des cartes géophysiques, levé magnétique aéroporté de la région de la Baie d'Ungava, Québec, SNRC 24 K/09","year":2010,"lang":"fr","type":"report","venue":"","topic":"Geological Modeling and Analysis","field":"Earth and Planetary Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Natural Resources Canada","funders":"","keywords":"Geology; Humanities; Art","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":[0.0005975605,0.0008935563,0.0007030549,0.004545296,0.001518024,0.001569182,0.0009365826,0.0004050292,0.02380122],"category_scores_gemma":[0.00133643,0.0004138795,0.0005438365,0.006340102,0.0004809106,0.0006676816,0.0004391856,0.0006671256,0.003685158],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01519871,"about_ca_system_score_gemma":0.02345495,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9893187,"about_ca_topic_score_gemma":0.994144,"domain_scores_codex":[0.9995246,0.00002818269,0.0000170645,0.00009087296,0.0002655042,0.00007387306],"domain_scores_gemma":[0.9987305,0.0001224833,0.00009561238,0.0001268398,0.0007680199,0.0001564939],"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":[0.0005734496,0.0002149257,0.1337457,0.0006985736,0.0003864684,0.0005064093,0.001552491,0.01582776,0.008832361,0.00718386,0.5928563,0.2376218],"study_design_scores_gemma":[0.00009586609,0.0000310563,0.6104911,0.00009183627,0.00004260361,0.0001347104,0.0006726492,0.008355878,0.003043617,0.0004495787,0.3765365,0.0000546574],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.1293744,0.003849748,0.008853656,0.001900963,0.0003849317,0.0005622327,0.7623222,0.002477222,0.09027456],"genre_scores_gemma":[0.3035736,0.003266133,0.03247996,0.000248529,0.0001685483,0.0006622241,0.2493296,0.0008027234,0.4094687],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.02380122,"threshold_uncertainty_score":0.1102749,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02625457425459272,"score_gpt":0.2480281374574216,"score_spread":0.2217735632028289,"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."}}