{"id":"W48780797","doi":"","title":"Tools and Methods for a Transportation Household Survey","year":2008,"lang":"en","type":"article","venue":"PolyPublie (École Polytechnique de Montréal)","topic":"Transportation Planning and Optimization","field":"Social Sciences","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Public transport; Survey data collection; Travel survey; Transport engineering; Transportation planning; Computer science; Intelligent transportation system; Software; Sample (material); Planner; Travel behavior; Task (project management); Operations research; Engineering; Systems engineering","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":[0.00167571,0.0001450645,0.0002102968,0.0001675959,0.0007315541,0.00008980093,0.0001498753,0.0002113122,0.00001093635],"category_scores_gemma":[0.0004409883,0.0001596339,0.0000733965,0.0003823108,0.0001512172,0.0004234057,0.000003371628,0.0001263112,7.088579e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008738655,"about_ca_system_score_gemma":0.0002373264,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.01930877,"about_ca_topic_score_gemma":0.02569388,"domain_scores_codex":[0.9985828,0.0002903008,0.0003032475,0.0002730122,0.0001855916,0.0003650929],"domain_scores_gemma":[0.9987911,0.0005665622,0.0001338728,0.0001704589,0.0001434913,0.0001944868],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003634396,0.0002156924,0.8440859,0.00005502587,0.00006963911,0.00001951401,0.02149421,0.01214926,0.00116232,0.05461273,0.004301046,0.06147121],"study_design_scores_gemma":[0.0004972902,0.00006667102,0.9764576,0.00001730035,0.0000289177,0.000004702702,0.0003637577,0.00641676,0.0007165545,0.0008324568,0.01431576,0.0002822184],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1560602,0.0003975227,0.8410229,0.0008296306,0.00008125098,0.0006366838,0.0003491517,0.0004379054,0.0001847823],"genre_scores_gemma":[0.6088499,0.0006538449,0.3885281,0.000531946,0.00006040517,0.0002792233,0.0003892355,0.00003067099,0.0006766459],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.4527898,"threshold_uncertainty_score":0.9920847,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04870422374430391,"score_gpt":0.3170527857244906,"score_spread":0.2683485619801867,"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."}}