{"id":"W4408603065","doi":"10.1117/12.3041220","title":"Multispectral optical sensor for psychological stress detection","year":2025,"lang":"en","type":"article","venue":"","topic":"Infrared Thermography in Medicine","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Multispectral image; Computer science; Stress (linguistics); Computer vision; Artificial intelligence","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.0003931543,0.0005057021,0.0003247044,0.0004967125,0.0001820945,0.0002782404,0.0003894824,0.0007441325,0.001602882],"category_scores_gemma":[0.0003241907,0.0002155084,0.0002923518,0.0003296605,0.0001636509,0.0004358507,0.0003678353,0.0004455381,0.0004454096],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002097638,"about_ca_system_score_gemma":0.0001300549,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003519616,"about_ca_topic_score_gemma":0.0008917098,"domain_scores_codex":[0.9996346,0.00008159758,0.000009959874,0.0001118776,0.0001338608,0.00002802057],"domain_scores_gemma":[0.9998155,0.00006670325,0.00004010477,0.00001672756,0.00004460658,0.00001649196],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00008027288,0.00004908812,0.0008705984,0.00009981093,0.00001688113,0.00002893464,0.00002435725,0.0002367036,0.9822286,0.00009296138,0.0001801052,0.01609168],"study_design_scores_gemma":[0.00002260116,0.0007488225,0.01763312,0.00003857581,0.00009748038,0.001000287,0.0001162156,0.02405967,0.951238,0.0003347158,0.004649942,0.00006058903],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6633425,0.01243229,0.3161925,0.0005112967,0.0003198457,0.0002099523,0.0008464938,0.001100497,0.005044542],"genre_scores_gemma":[0.80603,0.003050168,0.1863131,0.0005605616,0.0001203344,0.0002009181,0.0002359693,0.00004324772,0.003445749],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001602882,"threshold_uncertainty_score":0.005362213,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01577206515016347,"score_gpt":0.3520997868868178,"score_spread":0.3363277217366543,"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."}}