{"id":"W6920107115","doi":"10.6068/dp14ba8d4584e14","title":"Most Recent Data (2003). Statistics Canada. CANSIM: Environment - Natural Resources | Country: Canada | Table: Survey of innovation, selected service industries, percentage of total revenues from the sale of products to the mining and/or forestry and/or forest products industries | Variable: Mining industry, Office machinery and equipment rental and leasing, 10% to 24% of revenues, Innovative business units | Units: %, 2003. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. Dataset-ID: 075-001-086.","year":2015,"lang":"en","type":"other","venue":"Data Planet","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Economic statistics; Revenue; Official statistics; Natural resource; Census; Summary statistics; Descriptive statistics; Service (business)","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":["metaresearch","metaepi_narrow","bibliometrics"],"consensus_categories":[],"category_scores_codex":[0.002061454,0.0007603675,0.001231304,0.0001860892,0.0001781851,0.0001312464,0.001747563,0.0004823847,0.0001070706],"category_scores_gemma":[0.03202091,0.0005693513,2.927936e-8,0.02106289,0.0006416607,0.000352597,0.003001002,0.001042179,6.015977e-7],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002150178,"about_ca_system_score_gemma":0.0582159,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9974406,"about_ca_topic_score_gemma":0.9933282,"domain_scores_codex":[0.9940063,0.0009940027,0.001623348,0.001366746,0.001400685,0.0006089121],"domain_scores_gemma":[0.9815208,0.001023491,0.002283653,0.002884657,0.01204778,0.0002395933],"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":[0.001474746,0.0000917943,0.00411069,0.0007891476,0.0004601932,0.00003949986,0.00009394999,0.00002964006,0.00009042231,0.00001191094,0.9924256,0.0003823959],"study_design_scores_gemma":[0.0008731823,0.0001843833,0.005353502,0.0006512775,0.0003486262,0.0001046121,0.002027002,0.0002769452,0.000003931875,1.004063e-8,0.989597,0.0005795321],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.004400089,0.002782946,9.269986e-7,0.00003916609,0.0002867553,0.001778465,0.990681,0.00001540273,0.00001523844],"genre_scores_gemma":[0.0006127504,0.0004319535,0.0005596393,0.0001489962,0.0001443589,0.00001771848,0.9971573,0.0001999129,0.0007274012],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.05800088,"threshold_uncertainty_score":0.9997449,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04687640877163237,"score_gpt":0.2496186275033995,"score_spread":0.2027422187317671,"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."}}