{"id":"W6964253107","doi":"10.25318/2710035401-fra","title":"Dépenses moyennes au titre de la recherche et développement intra-muros des entreprises, selon le pays de contrôle et la taille de l'effectif","year":2019,"lang":"fr","type":"dataset","venue":"Statistics Canada Dissemination","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Context (archaeology); Power (physics); Limiting; Closure (psychology)","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":[0.002247411,0.0012445,0.001580674,0.007656051,0.001199504,0.002878382,0.002025716,0.001000743,0.03766511],"category_scores_gemma":[0.0271215,0.0006307795,0.001328043,0.01800081,0.0006292009,0.001365387,0.001493728,0.001823171,0.01779623],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.009793592,"about_ca_system_score_gemma":0.02767161,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8553323,"about_ca_topic_score_gemma":0.897536,"domain_scores_codex":[0.996973,0.0003914124,0.0003821403,0.0005563368,0.00120739,0.0004896753],"domain_scores_gemma":[0.9827014,0.005036274,0.001563124,0.001227192,0.008589597,0.0008824697],"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":[0.0001074033,0.00001635418,0.01574323,0.001169655,0.0001056722,0.00002857938,0.0001626904,0.0002958999,0.00004951207,0.001340163,0.9726239,0.008356945],"study_design_scores_gemma":[0.0001414986,0.00001821281,0.08321083,0.001264455,0.0001657526,0.00007176083,0.0007026908,0.0003427324,0.0003110156,0.0008206627,0.9128909,0.00005963344],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0006187106,0.0004746025,0.0000888925,0.0002215745,0.00003913951,0.00001400491,0.9962053,0.0001056744,0.002232045],"genre_scores_gemma":[0.006489003,0.001231998,0.0006535782,0.0002157265,0.00004624909,0.0001684205,0.9824186,0.0001424404,0.008633928],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1446677,"threshold_uncertainty_score":0.2910394,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04318638061865749,"score_gpt":0.3587112201775115,"score_spread":0.315524839558854,"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."}}