{"id":"W6963142242","doi":"10.18164/c5c1db53-a17e-47e8-b499-7b05ce385640","title":"Montreal ACES mobile surveys 2023","year":2023,"lang":"en","type":"dataset","venue":"ECCC Data Catalogue","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"GDG Environnement; Government of Canada; Gouvernement du Québec; Environment and Climate Change Canada","funders":"","keywords":"Metropolitan area; Atmospheric composition; Global Positioning System; Air pollution; Atmospheric temperature; Weather station; Urban park","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005950789,0.0021465,0.001004093,0.003486687,0.0009178206,0.002018513,0.002765876,0.0009138119,0.06832679],"category_scores_gemma":[0.002892695,0.000692374,0.0008119212,0.009277405,0.0003126429,0.0009880343,0.001262651,0.001188525,0.07883976],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00401489,"about_ca_system_score_gemma":0.004753027,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.6213761,"about_ca_topic_score_gemma":0.702666,"domain_scores_codex":[0.9992251,0.00006495709,0.00003922377,0.0001877243,0.0003041154,0.0001788813],"domain_scores_gemma":[0.9983797,0.0001159913,0.0001238236,0.0003476276,0.0008338393,0.0001990693],"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":[0.00002263164,0.000005945006,0.000613413,0.0000880035,0.0000106077,0.00001014082,0.00001500495,0.0001635973,0.00005654812,0.0002649098,0.996795,0.001954278],"study_design_scores_gemma":[0.00006049623,0.00000669065,0.008904743,0.00008104637,0.000009979541,0.00001662963,0.00005852457,0.0006065638,0.0002477728,0.0004090229,0.9895751,0.00002353905],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001226292,0.00002010992,0.00005548187,0.00002285772,0.000009221853,0.000008079939,0.9984054,0.0003133099,0.001043022],"genre_scores_gemma":[0.0003874223,0.00002300322,0.0002032459,0.00001500661,0.000004088433,0.0000306344,0.9980963,0.00008857302,0.001151829],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.3786239,"threshold_uncertainty_score":0.7617074,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0639355493086932,"score_gpt":0.3256767355293035,"score_spread":0.2617411862206103,"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."}}