{"id":"W6963937316","doi":"10.25318/2710033601-fra","title":"Dépenses au titre de la recherche et développement intra-muros des entreprises, selon le pays de contrôle et le groupe des dépenses en recherche et développement","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); Research methodology; Power (physics)","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":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.001416888,0.001238465,0.001328569,0.008243198,0.001119389,0.002853131,0.001722939,0.00102571,0.0425465],"category_scores_gemma":[0.01798079,0.0006462092,0.001125464,0.02159337,0.0004747602,0.001400735,0.001453393,0.001758651,0.02327853],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.009530179,"about_ca_system_score_gemma":0.0210384,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.803133,"about_ca_topic_score_gemma":0.8610592,"domain_scores_codex":[0.9975604,0.0002486466,0.0003670395,0.0004460642,0.0009505528,0.0004274136],"domain_scores_gemma":[0.988429,0.002663845,0.001183578,0.0008348471,0.006247912,0.0006408254],"domain_codex":null,"domain_gemma":"incentives","domain_candidate":"incentives","domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00006403423,0.00001076604,0.007785232,0.0008339354,0.00005404311,0.00002018629,0.00008146402,0.0001827195,0.00003699985,0.0008992448,0.9858117,0.004219673],"study_design_scores_gemma":[0.0001093994,0.00001080228,0.05754222,0.0008573256,0.00007528591,0.00005355935,0.0004756184,0.0002315966,0.0002136007,0.0005658039,0.9398203,0.00004448228],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0002552622,0.0001616201,0.00002868394,0.0001076519,0.00001872328,0.000006881409,0.9980898,0.00004650529,0.001284736],"genre_scores_gemma":[0.002137147,0.0004444344,0.0002671468,0.00009404827,0.00001693511,0.00007901507,0.992703,0.00004913706,0.004209233],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.9985831,"threshold_uncertainty_score":0.3960527,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1430222901724955,"score_gpt":0.4025715191612323,"score_spread":0.2595492289887369,"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."}}