{"id":"W4296078656","doi":"10.29173/mocs268","title":"Environment-aware worker trajectory prediction using surveillance camera on modular construction sites","year":2022,"lang":"en","type":"article","venue":"Modular and Offsite Construction (MOC) Summit Proceedings","topic":"Occupational Health and Safety Research","field":"Health Professions","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada; Alberta Innovates","keywords":"Exploit; Modular design; Trajectory; Computer science; Scheme (mathematics); Data mining; Artificial intelligence; Machine learning; Simulation; Real-time computing; Computer security","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002360244,0.000952503,0.0005913824,0.0007471044,0.0002446577,0.0004337532,0.0007923794,0.0005278687,0.0007293205],"category_scores_gemma":[0.0007603684,0.0002169928,0.0004541102,0.0009188924,0.0002024946,0.0005433876,0.0005905502,0.00059523,0.0005200357],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003736618,"about_ca_system_score_gemma":0.0005413934,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02152741,"about_ca_topic_score_gemma":0.02748477,"domain_scores_codex":[0.9998114,0.00002539202,0.000005850438,0.00008005639,0.00003970032,0.00003771875],"domain_scores_gemma":[0.9997594,0.0000570101,0.00004204042,0.00004277024,0.00006521471,0.00003356632],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.0004205648,0.0001892983,0.03856227,0.0001185119,0.00007552125,0.0003884851,0.000119718,0.7912697,0.007787339,0.000570996,0.003997136,0.1565005],"study_design_scores_gemma":[0.000003254253,0.00002460921,0.004370461,0.000006860393,0.000005616982,0.00002277261,0.00003108316,0.9942677,0.0007989651,0.0001973639,0.0002664612,0.000004722072],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7450354,0.001420855,0.2454755,0.0003042448,0.0001423456,0.0000789908,0.002691606,0.001786405,0.003064575],"genre_scores_gemma":[0.9674896,0.0004183021,0.0273268,0.00002710984,0.00002960242,0.00003186276,0.003377335,0.00002984034,0.001269455],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02152741,"threshold_uncertainty_score":0.04280424,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04285407264216739,"score_gpt":0.3264422224259971,"score_spread":0.2835881497838297,"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."}}