{"id":"W4402438648","doi":"10.11159/icmie24.102","title":"Analysis Of Improvements In The Practice Of Anthropometry Through 3D Scanning And Photogrammetry At UNITEC","year":2024,"lang":"en","type":"article","venue":"Proceedings of the World Congress on Mechanical, Chemical, and Material Engineering","topic":"Occupational Health and Safety in Workplaces","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Photogrammetry; 3d scanning; Anthropometry; Computer science; Computer vision; Artificial intelligence; Computer graphics (images); Geography; Archaeology","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":[0.002601956,0.0003772549,0.0003089867,0.001504221,0.0003554647,0.0005429638,0.0004939886,0.0004030466,0.001108728],"category_scores_gemma":[0.006696308,0.0002323793,0.0002783047,0.001462881,0.0003282493,0.0002949763,0.0006333807,0.0003554959,0.0003894329],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008197328,"about_ca_system_score_gemma":0.0009860675,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004821304,"about_ca_topic_score_gemma":0.006279672,"domain_scores_codex":[0.9952011,0.001817947,0.0002668238,0.0005577702,0.001789256,0.0003670341],"domain_scores_gemma":[0.9939879,0.001717448,0.001176829,0.0005473827,0.002177087,0.0003933026],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0008472772,0.001141377,0.5005341,0.0005990936,0.00009893414,0.0007137899,0.007355293,0.002813824,0.02537253,0.0002078127,0.001036377,0.4592796],"study_design_scores_gemma":[0.000007885707,0.0009033605,0.9889287,0.00004299052,0.00002639355,0.000183526,0.001262694,0.001292578,0.004448259,0.00003281403,0.002852821,0.0000179774],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9937053,0.0003254352,0.003785281,0.0001459278,0.00001716964,0.00009221841,0.0002213976,0.00008522825,0.001622032],"genre_scores_gemma":[0.9904872,0.0003445602,0.007205561,0.00002779385,0.00002241819,0.00006860209,0.0002843068,0.00002530362,0.001534234],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004821304,"threshold_uncertainty_score":0.01376063,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01597324766538756,"score_gpt":0.3505090292869864,"score_spread":0.3345357816215989,"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."}}