{"id":"W6945229026","doi":"10.25318/2110022601-eng","title":"Software development and computer services, summary statistics, by North American Industry Classification System (NAICS), inactive","year":2020,"lang":"en","type":"dataset","venue":"Statistics Canada Dissemination","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Table (database); Software; Software development; Data collection; Computer software; Profit margin","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002006602,0.0008897529,0.0008940734,0.0002635251,0.0004314689,0.0002733655,0.000559491,0.0003676827,0.00001527175],"category_scores_gemma":[0.0002221372,0.001060135,0.00001854257,0.0007661242,0.0002286039,0.0001719289,0.0002428232,0.001357836,0.0000815694],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004530242,"about_ca_system_score_gemma":0.002465989,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.1995766,"about_ca_topic_score_gemma":0.8628443,"domain_scores_codex":[0.9951385,0.0002914396,0.00110371,0.001178961,0.001651655,0.0006357312],"domain_scores_gemma":[0.9952772,0.0007329282,0.001890329,0.000558571,0.0008884225,0.0006525225],"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":[0.00005321519,0.00006818993,0.00106515,0.002606621,0.0002239873,0.0001435046,0.0001861112,0.000007109189,0.00000388189,0.00009958907,0.9786618,0.01688085],"study_design_scores_gemma":[0.0003433726,0.0001236122,0.1060819,0.000637451,0.0004348488,0.00001876162,0.002249942,0.001799908,0.00003876268,0.000004780776,0.8867509,0.00151578],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0004284719,0.00005800983,0.02004938,0.0000287091,0.0004753752,0.0008268459,0.9780087,0.0001203713,0.000004107404],"genre_scores_gemma":[0.001209675,0.00004534035,0.02643019,0.0001884343,0.0001673592,0.0001604165,0.9715794,0.0001703369,0.00004883611],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.6632677,"threshold_uncertainty_score":0.9992912,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00762093961923118,"score_gpt":0.2355143417216872,"score_spread":0.227893402102456,"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."}}