{"id":"W4391065551","doi":"10.1016/j.trpro.2023.12.091","title":"Workshop Synthesis: Activity Tracker and Data Enrichment – Connecting Transport and Health","year":2024,"lang":"en","type":"article","venue":"Transportation research procedia","topic":"Human Mobility and Location-Based Analysis","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University","funders":"","keywords":"Computer science; Transport engineering; Environmental science; Engineering","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":[],"consensus_categories":[],"category_scores_codex":[0.006347857,0.00009828094,0.0001751234,0.0002011242,0.0008845389,0.0001682224,0.000207128,0.00008496341,0.000168569],"category_scores_gemma":[0.0002402873,0.00009637977,0.00002688269,0.0007012236,0.0003265241,0.0005427853,0.000006587844,0.0003663833,0.000009033102],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008323088,"about_ca_system_score_gemma":0.0007375905,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.01091246,"about_ca_topic_score_gemma":0.135813,"domain_scores_codex":[0.9978809,0.0002195196,0.0002407103,0.0005922149,0.0006820773,0.000384614],"domain_scores_gemma":[0.9986697,0.0006911597,0.00003409982,0.0002254621,0.0001299869,0.0002495906],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.00007070411,0.0002911541,0.02802929,0.002175801,0.0002040979,0.00003754949,0.1669985,0.00005756216,0.0001399377,0.02799233,0.001703971,0.7722991],"study_design_scores_gemma":[0.0006353872,0.0001789198,0.7880414,0.001315978,0.0002678566,0.000001553699,0.1063193,0.01081864,0.0002522703,0.004597838,0.08673576,0.0008351749],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9654811,0.003138326,0.003576041,0.02585538,0.00006601763,0.0008754074,0.0001564086,0.0003093372,0.0005420113],"genre_scores_gemma":[0.9974195,0.001810561,0.0002068136,0.00005428364,0.0001181358,0.00008346984,0.00008914483,0.00001622965,0.0002017988],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7714639,"threshold_uncertainty_score":0.995674,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2376776982030709,"score_gpt":0.4966800409739041,"score_spread":0.2590023427708332,"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."}}