{"id":"W4408749021","doi":"10.1016/j.autcon.2025.106130","title":"Safety-constrained Deep Reinforcement Learning control for human–robot collaboration in construction","year":2025,"lang":"en","type":"article","venue":"Automation in Construction","topic":"Occupational Health and Safety Research","field":"Health Professions","cited_by":15,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia","funders":"Campbell Soup Company; Natural Sciences and Engineering Research Council of Canada; China Scholarship Council","keywords":"Reinforcement learning; Control (management); Artificial intelligence; Robot; Reinforcement; Engineering; Computer science; Construction site safety; Human–computer interaction; Construction engineering; Structural engineering","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"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":[0.001213033,0.0007600865,0.0008801265,0.0002287055,0.0004968873,0.0006338653,0.001176844,0.001279548,0.002279991],"category_scores_gemma":[0.002706044,0.000498347,0.0003714772,0.0001852802,0.0009965455,0.000684098,0.00179575,0.001538023,0.00026015],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008932073,"about_ca_system_score_gemma":0.001519832,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01053824,"about_ca_topic_score_gemma":0.009264905,"domain_scores_codex":[0.9995632,0.0001200627,0.00001489186,0.0001161014,0.00007789907,0.0001078414],"domain_scores_gemma":[0.9985941,0.0007561874,0.0001668583,0.00008681894,0.0002611568,0.0001347744],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001261511,0.00007375318,0.000420927,0.00004170724,0.00002090542,0.00004158396,0.00006851383,0.9710997,0.001495287,0.002661271,0.0005985867,0.02335155],"study_design_scores_gemma":[0.000004985527,0.0000195235,0.00005609365,0.000002251585,0.000001880922,0.00000252889,0.000003536138,0.9988769,0.00015376,0.000814374,0.00006264578,0.000001616984],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06820588,0.0003871861,0.9267034,0.0003581689,0.00009049858,0.00004925158,0.00004596035,0.0004688117,0.003690877],"genre_scores_gemma":[0.9820331,0.00004845419,0.01605931,0.00006358005,0.00001867466,0.00004676114,0.00003391058,0.00002496623,0.001671133],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01053824,"threshold_uncertainty_score":0.02095383,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02763601205076397,"score_gpt":0.4358170557865518,"score_spread":0.4081810437357878,"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."}}