{"id":"W4214806942","doi":"10.36227/techrxiv.17004538.v2","title":"TFW: Annotated Thermal Faces in the Wild Dataset","year":2022,"lang":"en","type":"preprint","venue":"","topic":"Face recognition and analysis","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Computer science; Landmark; Face (sociological concept); Benchmark (surveying); Minimum bounding box; Artificial intelligence; Bounding overwatch; Code (set theory); Face detection; Pattern recognition (psychology); Computer vision; Object detection; Facial recognition system; Set (abstract data type); Image (mathematics); Machine learning; Cartography; Geography","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":[0.0007636062,0.002525871,0.00124663,0.001866301,0.0008352948,0.0008105201,0.002310866,0.001667754,0.01674069],"category_scores_gemma":[0.001955207,0.0004681085,0.001347697,0.001307117,0.0005156369,0.0008654993,0.001379204,0.001342721,0.01760927],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008398612,"about_ca_system_score_gemma":0.0006931743,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01328442,"about_ca_topic_score_gemma":0.02939971,"domain_scores_codex":[0.9991392,0.0001023988,0.00005380875,0.0002626438,0.00030823,0.0001336251],"domain_scores_gemma":[0.9994338,0.00009490346,0.00004218997,0.0002223146,0.0001607136,0.00004608366],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001140777,0.0004782923,0.005208255,0.001253364,0.0002360305,0.0007259042,0.0001659909,0.003764265,0.01702658,0.001184133,0.8498016,0.1190148],"study_design_scores_gemma":[0.0008592489,0.00111584,0.1345391,0.001111823,0.0004114498,0.01205168,0.00121096,0.08809456,0.04706899,0.007446505,0.705584,0.0005058603],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0733175,0.003994751,0.0332519,0.0006316269,0.001127942,0.001242377,0.8466201,0.02291056,0.01690313],"genre_scores_gemma":[0.04471381,0.0004956417,0.02213177,0.000259542,0.00008984461,0.0008810236,0.9258043,0.0005976887,0.005026449],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.01674069,"threshold_uncertainty_score":0.05600315,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.035795837419091,"score_gpt":0.2891625563028222,"score_spread":0.2533667188837312,"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."}}