{"id":"W4220781100","doi":"10.31235/osf.io/ubszd","title":"Mapping Newcomers’ Commute in Calgary","year":2022,"lang":"en","type":"preprint","venue":"","topic":"Urban Transport and Accessibility","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Transit (satellite); Transport engineering; Business; Job creation; Settlement (finance); Marketing; Public transport; Labour economics; Engineering; Economics; Finance","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":[0.0003519741,0.000304292,0.0003492916,0.001688513,0.001265247,0.001482456,0.0009323401,0.0004859609,0.003561885],"category_scores_gemma":[0.001258231,0.0002035125,0.0002697133,0.002927888,0.0005404688,0.0005245933,0.002001744,0.0005459636,0.0005595866],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003367453,"about_ca_system_score_gemma":0.001857443,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.7299483,"about_ca_topic_score_gemma":0.8503702,"domain_scores_codex":[0.9996696,0.00004245018,0.00000895554,0.0000837656,0.00009086551,0.000104489],"domain_scores_gemma":[0.9993401,0.0001004896,0.00008761752,0.00005047898,0.0002696481,0.0001517425],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004033077,0.00008795036,0.8628151,0.0003626553,0.000122614,0.002421147,0.03014011,0.003710256,0.002281808,0.001447558,0.009161986,0.0870455],"study_design_scores_gemma":[0.000008502633,0.00003354538,0.9682329,0.00009835814,0.00001655331,0.00008639031,0.02043049,0.001010872,0.0001400091,0.0001154361,0.009814292,0.00001282171],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9876751,0.0006851581,0.0007014513,0.0002091989,0.00003192743,0.00008157963,0.001891312,0.00002744273,0.008696879],"genre_scores_gemma":[0.9869108,0.001141386,0.001662375,0.00008490323,0.00002066447,0.00006889208,0.002412279,0.00002535263,0.007673339],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2700517,"threshold_uncertainty_score":0.5432841,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06511428064970332,"score_gpt":0.3390261066632416,"score_spread":0.2739118260135383,"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."}}