{"id":"W4399371626","doi":"10.1016/j.trip.2024.101116","title":"Using Facebook to Recruit Urban Participants for Smartphone-Based Travel Surveys","year":2024,"lang":"en","type":"article","venue":"Transportation Research Interdisciplinary Perspectives","topic":"Human Mobility and Location-Based Analysis","field":"Social Sciences","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Transport Canada","funders":"University of New South Wales","keywords":"Social media; Advertising; Smartphone application; Internet privacy; Analytics; Population; Business; Marketing; Computer science; World Wide Web; Data science; Multimedia; Sociology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["sts","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.006885875,0.0001674764,0.0002474106,0.0006876468,0.001495226,0.0002971096,0.0003329345,0.0001123278,0.001493465],"category_scores_gemma":[0.0002400385,0.0001691244,0.0002571192,0.001271157,0.000610017,0.0003085598,0.00001540744,0.000310527,0.0001185744],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006689699,"about_ca_system_score_gemma":0.001028926,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003249169,"about_ca_topic_score_gemma":0.05925844,"domain_scores_codex":[0.9962099,0.001146323,0.0003896201,0.0007171364,0.0007921408,0.0007448535],"domain_scores_gemma":[0.9975447,0.001078203,0.0000344903,0.0002619708,0.0007134001,0.0003672574],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.0004766215,0.0006513527,0.004049222,0.0003260394,0.0003119913,0.00003401597,0.9307903,0.006279563,0.005657849,0.03338144,0.004043826,0.01399777],"study_design_scores_gemma":[0.001029147,0.0009762959,0.1119647,0.0008331285,0.0002281454,2.113271e-7,0.8000565,0.05455444,0.003403819,0.01571812,0.01025273,0.0009827082],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6897415,0.0004283105,0.2862018,0.01561467,0.000315665,0.003542955,0.0004231507,0.0002732273,0.003458764],"genre_scores_gemma":[0.9950407,0.0000123044,0.0006698304,0.00002623868,0.0002857736,0.0007531693,0.00007624352,0.00003239092,0.003103362],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3052992,"threshold_uncertainty_score":0.9998047,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3227525211160218,"score_gpt":0.5347851333266832,"score_spread":0.2120326122106614,"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."}}