{"id":"W2065202517","doi":"10.1002/atr.5670360104","title":"Impact of interviewing by proxy in travel survey conducted by telephone","year":2002,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Human Mobility and Location-Based Analysis","field":"Social Sciences","cited_by":30,"is_retracted":false,"has_abstract":true,"ca_institutions":"Transport Canada","funders":"","keywords":"TRIPS architecture; Interview; Proxy (statistics); Sample (material); Data collection; Telephone interview; Transport engineering; Survey data collection; Business; Geography; Statistics; Engineering; Mathematics; Political science; Sociology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.2093169,0.0008664139,0.001385098,0.002126233,0.002023533,0.003862287,0.002328584,0.001377285,0.005882513],"category_scores_gemma":[0.5002274,0.0006974094,0.001385266,0.004865175,0.002783448,0.002903583,0.006048895,0.002347391,0.001139914],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004580521,"about_ca_system_score_gemma":0.005198477,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01266708,"about_ca_topic_score_gemma":0.009883555,"domain_scores_codex":[0.3190419,0.6265602,0.01966239,0.007293373,0.02449798,0.002944184],"domain_scores_gemma":[0.2656918,0.6430426,0.04568871,0.02867561,0.01421794,0.002683311],"domain_codex":"methods","domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.006035169,0.0008172494,0.6698624,0.005937306,0.0007709461,0.001618276,0.03528914,0.003648207,0.001824386,0.01228359,0.01099717,0.2509161],"study_design_scores_gemma":[0.0004997743,0.007067537,0.7851903,0.01021296,0.001669155,0.004488293,0.07112234,0.03425368,0.01016319,0.007095009,0.06778934,0.000448341],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.801169,0.01583295,0.09768663,0.01074399,0.003225122,0.008369732,0.005658401,0.0005112429,0.0568028],"genre_scores_gemma":[0.9658601,0.001796548,0.02356497,0.002143184,0.0002750424,0.003530357,0.0009461606,0.0001018077,0.001781796],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2093169,"threshold_uncertainty_score":0.9750531,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03203829477773317,"score_gpt":0.3291637087143776,"score_spread":0.2971254139366444,"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."}}