{"id":"W6939102920","doi":"10.6068/dp14ba81fc60655","title":"Trend 1990 - 2008. Statistics Canada. CANSIM: Environment - Air and Climate | Country: Canada | Table: Direct plus indirect greenhouse gas emissions intensity, by industry | Variable: Non-profit sports and recreation clubs, Index, 1990=100 | Units: , 1990-2008. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. Dataset-ID: 075-001-083.","year":2015,"lang":"en","type":"other","venue":"Data Planet","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Recreation; Economic statistics; Official statistics; Census; Summary statistics; Greenhouse gas; Descriptive statistics; Statistical analysis","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":[0.001823484,0.002167108,0.002435755,0.007442026,0.002733264,0.004457336,0.004562329,0.001406083,0.0925279],"category_scores_gemma":[0.01500653,0.001707646,0.002103814,0.03868669,0.0005934516,0.00264054,0.002249992,0.003108256,0.05690913],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.04777053,"about_ca_system_score_gemma":0.1305572,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9936982,"about_ca_topic_score_gemma":0.9910491,"domain_scores_codex":[0.996147,0.0002451032,0.0004139094,0.0004818657,0.001806624,0.0009054062],"domain_scores_gemma":[0.9705075,0.0009543968,0.0008505387,0.0008213171,0.02551189,0.001354275],"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":[0.0000195322,0.000005414072,0.0008805003,0.000256832,0.0000191804,0.000006367021,0.00001842573,0.0001050697,0.000009262832,0.0003614576,0.9967909,0.001526941],"study_design_scores_gemma":[0.0001349525,0.0000107897,0.0202274,0.0007831065,0.00006679947,0.00002599928,0.0003890058,0.0004402866,0.000168904,0.0006400917,0.9770381,0.00007458476],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004772535,0.00005258141,0.00002681751,0.0001253685,0.00002936935,0.00001375868,0.9985644,0.00006565747,0.001074311],"genre_scores_gemma":[0.0009308632,0.0003318831,0.0004323247,0.0001735354,0.00001898605,0.0001313192,0.9933457,0.0001462785,0.004489074],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.0925279,"threshold_uncertainty_score":0.3466011,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02051490652772598,"score_gpt":0.2352534496139086,"score_spread":0.2147385430861827,"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."}}