{"id":"W6888939766","doi":"10.25318/2710021301-eng","title":"Innovation, logging and manufacturing industries, percentage of plants with full-time employees who were involved in research and development activities","year":2019,"lang":"en","type":"dataset","venue":"Statistics Canada Dissemination","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Logging; Wood industry; Forest industry; Manufacturing; Production (economics)","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":[0.001171301,0.001540987,0.001564417,0.005327354,0.001278573,0.002048505,0.003312076,0.001250697,0.03693801],"category_scores_gemma":[0.008807337,0.0009264471,0.001331693,0.01467854,0.0003757152,0.001200844,0.001260116,0.001849355,0.01941908],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.009211311,"about_ca_system_score_gemma":0.01664319,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8662264,"about_ca_topic_score_gemma":0.8876862,"domain_scores_codex":[0.9985281,0.00009060211,0.000220552,0.000284694,0.0005239806,0.0003519796],"domain_scores_gemma":[0.990637,0.0008432595,0.000903948,0.0004953436,0.006433797,0.0006865263],"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":[0.0000505744,0.00002025112,0.004668975,0.0004659981,0.00003690967,0.00001318517,0.00002397136,0.0001763739,0.00003028235,0.0003424808,0.9929696,0.001201238],"study_design_scores_gemma":[0.0005913483,0.00003635925,0.1621165,0.0008911492,0.0001423822,0.0000646105,0.0004775446,0.000766105,0.0003911974,0.0005903619,0.8338494,0.00008304741],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001386243,0.00002266967,0.00001758171,0.00002658118,0.000009653048,0.000009293538,0.9994642,0.00002198504,0.0002893835],"genre_scores_gemma":[0.0008372923,0.00007291143,0.0001326515,0.00004428552,0.00000747569,0.0000853004,0.9972724,0.00001791094,0.001529714],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.9988287,"threshold_uncertainty_score":0.2691227,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04090300710436334,"score_gpt":0.310353771450554,"score_spread":0.2694507643461907,"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."}}