{"id":"W3109413066","doi":"10.5683/sp/deqjgq","title":"GTA Bike Surveys - Summer 2018 - Uncalibrated data","year":2018,"lang":"en","type":"dataset","venue":"Borealis","topic":"Air Quality Monitoring and Forecasting","field":"Environmental Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Analyser; Trailer; Environmental science; Meteorology; Geography; Remote sensing; Computer science","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":[0.0008670404,0.001824193,0.001076853,0.002118018,0.0006571527,0.001136411,0.001867838,0.001381052,0.008701553],"category_scores_gemma":[0.002485514,0.0005412545,0.0008895582,0.00371653,0.0004049379,0.0009332039,0.001161841,0.001224987,0.02097966],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001045238,"about_ca_system_score_gemma":0.001837616,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0643431,"about_ca_topic_score_gemma":0.1243804,"domain_scores_codex":[0.9991248,0.00008790939,0.00009268926,0.0002511167,0.0002821583,0.000161288],"domain_scores_gemma":[0.998435,0.00009674218,0.0001769922,0.0004730739,0.0006606074,0.0001576196],"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":[0.0003065148,0.0001330136,0.01343235,0.0005536447,0.0001004307,0.0001043815,0.0001264535,0.001738202,0.001128754,0.0003704547,0.9752284,0.006777206],"study_design_scores_gemma":[0.000365939,0.00007526989,0.1026732,0.000179028,0.00006751681,0.0001325604,0.0003248617,0.003132705,0.001928673,0.0006574765,0.8903879,0.00007481281],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.003832232,0.00006777398,0.0001767578,0.00005863123,0.00005746952,0.00002284966,0.9939063,0.0009732022,0.0009047504],"genre_scores_gemma":[0.002393856,0.00002299186,0.0003052902,0.00001497925,0.00001063148,0.00004564708,0.9966393,0.0000637765,0.0005034395],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.9356569,"threshold_uncertainty_score":0.1279371,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.109709603530888,"score_gpt":0.3176301601097378,"score_spread":0.2079205565788498,"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."}}