{"id":"W7008006946","doi":"","title":"Assessing the commercial use of transit smart card in Montréal","year":2010,"lang":"en","type":"other","venue":"PolyPublie (École Polytechnique de Montréal)","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Smart card; Transit (satellite); Public transport; Postal service; Automation; Key (lock); Work (physics)","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":[0.0005728432,0.0005675677,0.000179316,0.002270998,0.001109851,0.001626433,0.0011018,0.0003365327,0.01363668],"category_scores_gemma":[0.002542425,0.0002499083,0.0003114319,0.003609295,0.0005013429,0.0006039494,0.0008284837,0.0004311386,0.001234622],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01668333,"about_ca_system_score_gemma":0.01342001,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9884422,"about_ca_topic_score_gemma":0.9948279,"domain_scores_codex":[0.9994456,0.00005871325,0.00001948985,0.0000837859,0.0002830969,0.0001091944],"domain_scores_gemma":[0.9982179,0.00009707368,0.0002214125,0.00005208467,0.001134205,0.0002773467],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002352577,0.0002033216,0.8576518,0.00021468,0.0001946131,0.0004563382,0.002511408,0.002677709,0.001447026,0.003170589,0.05385428,0.07738301],"study_design_scores_gemma":[0.000009232194,0.0000398653,0.9731962,0.00003538113,0.00003758975,0.00003765803,0.0019105,0.001710744,0.0005844934,0.00004310261,0.02236713,0.00002804235],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8187358,0.001263933,0.001636772,0.00140861,0.00006590462,0.0004139027,0.05522984,0.0004033223,0.1208419],"genre_scores_gemma":[0.9134328,0.0008129714,0.001931075,0.0001217473,0.00001933507,0.0001197729,0.0138879,0.0001008976,0.06957342],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01668333,"threshold_uncertainty_score":0.1210466,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02275233925260967,"score_gpt":0.2658496666860116,"score_spread":0.243097327433402,"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."}}