{"id":"W3114418171","doi":"10.18280/i2m.190604","title":"Safety Monitoring and Evaluation of Construction Projects Based on Multi-sensor Fusion","year":2020,"lang":"en","type":"article","venue":"Instrumentation Mesure Métrologie","topic":"Occupational Health and Safety Research","field":"Health Professions","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Science Foundation of Shaanxi Province; Xi'an University of Architecture and Technology","keywords":"Wireless sensor network; Safety monitoring; Sensor fusion; Real-time computing; Data mining; Computer science; Data collection; Engineering; Systems engineering; Computer network; Artificial intelligence","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001099039,0.0006874468,0.0005803237,0.0008514966,0.0003525415,0.000602006,0.0006058825,0.0005577405,0.0003559637],"category_scores_gemma":[0.001696893,0.000211849,0.0006521909,0.0006877574,0.0004393131,0.001404482,0.0009688253,0.0005229134,0.00007375004],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005541077,"about_ca_system_score_gemma":0.0006713476,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002373512,"about_ca_topic_score_gemma":0.001805264,"domain_scores_codex":[0.9990086,0.0002079624,0.00005731272,0.0002410849,0.000403286,0.00008186877],"domain_scores_gemma":[0.9994426,0.0001458385,0.0001138714,0.00006438968,0.0002018317,0.00003137998],"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":[0.0002453731,0.0001585393,0.01934381,0.0001507405,0.0001182798,0.0001551707,0.0002599496,0.7840787,0.02379982,0.005963686,0.0007085515,0.1650174],"study_design_scores_gemma":[0.000003729278,0.00006250432,0.002799895,0.000004471191,0.00001599516,0.00002871474,0.00003811576,0.9919873,0.003348227,0.001517533,0.0001839534,0.000009651392],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1311672,0.0001350822,0.8670034,0.0001522596,0.00002691997,0.00004458236,0.00007153599,0.0002108628,0.001188057],"genre_scores_gemma":[0.9649025,0.0001378812,0.03422951,0.00002619663,0.00001368371,0.00004530435,0.00009820228,0.000009678205,0.0005370654],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002373512,"threshold_uncertainty_score":0.005812347,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2733649077676832,"score_gpt":0.5075342615869665,"score_spread":0.2341693538192832,"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."}}