{"id":"W4398839298","doi":"10.7910/dvn/qftapm","title":"Bus Stop Spacings for Transit Providers in Canada","year":2023,"lang":"en","type":"dataset","venue":"Harvard Dataverse","topic":"Transportation Planning and Optimization","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Transit (satellite); Transport engineering; Business; Computer science; Telecommunications; Engineering; Public transport","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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0003643788,0.0001526254,0.0002239859,0.0001500624,0.0002081019,0.00007168539,0.0003136648,0.0001607714,0.0006166779],"category_scores_gemma":[0.0002565378,0.000176526,0.00004511141,0.0003203663,0.00005301371,0.0002530032,0.000008213522,0.0001822298,0.002057933],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000442009,"about_ca_system_score_gemma":0.003504132,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9912675,"about_ca_topic_score_gemma":0.9990793,"domain_scores_codex":[0.99861,0.00006200147,0.0002614719,0.0003244818,0.0003936812,0.0003484319],"domain_scores_gemma":[0.999266,0.0001835862,0.0001222665,0.0002507605,0.00006580734,0.0001116402],"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":[0.00002902361,0.000009205453,0.00005561556,0.00009089999,0.00001389802,0.00004423907,0.0008252971,0.001862485,1.891122e-7,0.00004225287,0.9969229,0.0001040063],"study_design_scores_gemma":[0.0003653394,0.00000903673,0.000210735,0.00008129894,0.00004676815,1.740555e-7,0.003413037,0.00007449756,6.344342e-7,0.00001560241,0.9955786,0.0002043095],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00003815964,4.881103e-7,0.0001801069,0.0001098625,0.0008209075,0.000564609,0.9981596,0.00004900325,0.00007725594],"genre_scores_gemma":[0.00007112129,0.0001636849,0.0002380984,0.0002417781,0.0001078322,0.00006286402,0.9984866,0.00001668224,0.000611374],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.007811831,"threshold_uncertainty_score":0.9987191,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0199603718528182,"score_gpt":0.2599524075947785,"score_spread":0.2399920357419603,"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."}}