{"id":"W7006611841","doi":"","title":"Transforming Commercial Arterials into Bicycle Highways: Using Count Data","year":2023,"lang":"en","type":"article","venue":"PDXScholar  (Portland State University)","topic":"Urban Design and Spatial Analysis","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Count data; Pedestrian; Traffic count; Schema crosswalk; Modal; Data collection","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":[],"consensus_categories":[],"category_scores_codex":[0.0003176449,0.0001799341,0.0002813445,0.0004708404,0.0002669093,0.00009643583,0.0004542996,0.00007499843,0.00007048647],"category_scores_gemma":[0.00001312664,0.0001951937,0.00007096852,0.0009057464,0.0000365237,0.0008162218,0.00009715669,0.000180627,0.00008646644],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001061665,"about_ca_system_score_gemma":0.00004133522,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006140784,"about_ca_topic_score_gemma":0.0009748738,"domain_scores_codex":[0.9989197,0.00005090166,0.0002156269,0.0002762732,0.0002108512,0.0003267059],"domain_scores_gemma":[0.9993144,0.00003790665,0.00003899143,0.0004234209,0.00004266167,0.0001426479],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0008554875,0.0004594348,0.09205426,0.001178636,0.004815036,0.008438802,0.01994293,0.2424925,0.4551333,0.001115411,0.06305281,0.1104614],"study_design_scores_gemma":[0.001896381,0.00006140264,0.005074863,0.00007833968,0.0004824164,0.00001109709,0.0007713172,0.506901,0.003983548,0.0002189198,0.479472,0.001048759],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9666339,0.00004820304,0.03063745,0.00005053826,0.0002865944,0.0001378668,0.0002386726,0.0007177391,0.001249072],"genre_scores_gemma":[0.9979056,0.0003501758,0.0005533409,0.00002087077,0.00009743954,3.087493e-7,0.0004589819,0.0000347745,0.0005785768],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4511498,"threshold_uncertainty_score":0.7959768,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04756593912191431,"score_gpt":0.2235560899464924,"score_spread":0.1759901508245781,"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."}}