{"id":"W4304806953","doi":"10.3390/ijerph192013114","title":"Optimization of Work Environment and Community Labor Health Based on Digital Model—Empirical Evidence from Developing Countries","year":2022,"lang":"en","type":"article","venue":"International Journal of Environmental Research and Public Health","topic":"Digital Transformation in Industry","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Wuhan Polytechnic University","keywords":"Developing country; Work (physics); Empirical evidence; Occupational safety and health; Environmental health; Business; Psychology; Computer science; Economics; Medicine; Economic growth; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009727575,0.000288089,0.0002230677,0.001907311,0.0006840022,0.001663405,0.0004030201,0.0003270934,0.003752756],"category_scores_gemma":[0.002443345,0.0001728377,0.0007429156,0.002677658,0.0007596022,0.00123923,0.001020857,0.000416756,0.0002730242],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002618032,"about_ca_system_score_gemma":0.00167187,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.05006116,"about_ca_topic_score_gemma":0.04544271,"domain_scores_codex":[0.9995337,0.0001487047,0.00003178715,0.00007878057,0.00009311213,0.0001139902],"domain_scores_gemma":[0.9986199,0.0005625441,0.0003501948,0.000095045,0.0002220887,0.0001501203],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0000904819,0.0003286116,0.9510625,0.0001413724,0.0001438988,0.0002893226,0.001933706,0.006637905,0.0001182526,0.007044332,0.0008912465,0.03131839],"study_design_scores_gemma":[0.00001839379,0.0001554532,0.9629381,0.0001894645,0.0001496966,0.0001134144,0.01215216,0.0178219,0.0001922704,0.002488636,0.003756148,0.00002437332],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9871815,0.0008405112,0.001160516,0.0004151842,0.00001117185,0.00003766626,0.0003297374,0.000008116487,0.01001575],"genre_scores_gemma":[0.9988674,0.000355973,0.0002148886,0.00001791376,0.000002415695,0.000008195745,0.0001142251,0.000001435733,0.0004175444],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05006116,"threshold_uncertainty_score":0.09953958,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.153194948322298,"score_gpt":0.3607343659533233,"score_spread":0.2075394176310253,"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."}}