{"id":"W3174331430","doi":"10.1145/3463511","title":"NeckFace","year":2021,"lang":"en","type":"article","venue":"Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies","topic":"Emotion and Mood Recognition","field":"Psychology","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Computer science; Facial expression; Chin; Wearable computer; Computer vision; Artificial intelligence; Headphones; Match moving; Face (sociological concept); Pipeline (software); Facial muscles; Human–computer interaction; Motion (physics); Engineering; Psychology; Communication; Embedded system; Medicine","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":[0.0006025511,0.001488428,0.0007226108,0.0009534804,0.0004541715,0.001372516,0.001621259,0.001360581,0.1280315],"category_scores_gemma":[0.002486098,0.0004803638,0.0009030255,0.0004854965,0.000226543,0.002293748,0.002522351,0.0006245182,0.06830516],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004624081,"about_ca_system_score_gemma":0.0004877634,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001920745,"about_ca_topic_score_gemma":0.003845518,"domain_scores_codex":[0.9994585,0.00004213497,0.00004012487,0.0001610968,0.0002343325,0.00006371656],"domain_scores_gemma":[0.9996582,0.00006920467,0.00002589662,0.0001017391,0.0001145172,0.00003050373],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0007436257,0.00007593992,0.001843769,0.0008264994,0.00008768643,0.0003428096,0.0001816313,0.001509327,0.03842999,0.004560537,0.3968388,0.5545594],"study_design_scores_gemma":[0.0001269933,0.0003496149,0.008284465,0.0002868303,0.0001368831,0.002999897,0.0001933763,0.05795539,0.06407952,0.012036,0.8533834,0.0001676257],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02960726,0.005691494,0.4981315,0.0017132,0.003042286,0.001208027,0.04444569,0.2090308,0.2071298],"genre_scores_gemma":[0.231234,0.004299262,0.3126285,0.004024449,0.0006278638,0.001962243,0.09661841,0.01894983,0.3296554],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.1280315,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01953324686604767,"score_gpt":0.2979942208339685,"score_spread":0.2784609739679208,"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."}}