{"id":"W4312255352","doi":"10.1109/tim.2022.3232093","title":"Pig Face Recognition Based on Trapezoid Normalized Pixel Difference Feature and Trimmed Mean Attention Mechanism","year":2022,"lang":"en","type":"article","venue":"IEEE Transactions on Instrumentation and Measurement","topic":"Animal Behavior and Welfare Studies","field":"Veterinary","cited_by":38,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"China Postdoctoral Science Foundation; National Natural Science Foundation of China","keywords":"Artificial intelligence; Face (sociological concept); Pattern recognition (psychology); Pixel; Computer science; Feature (linguistics); Facial recognition system; Computer vision","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":[0.0005279535,0.0006511953,0.0009041585,0.001074599,0.0003438762,0.0005474657,0.001037976,0.0006033852,0.00251414],"category_scores_gemma":[0.0009613209,0.0002465312,0.0008411338,0.0005539427,0.0003462082,0.0008448163,0.0008745906,0.0006872451,0.0007991669],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004061015,"about_ca_system_score_gemma":0.0005192776,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00367312,"about_ca_topic_score_gemma":0.004333355,"domain_scores_codex":[0.9995265,0.00005030052,0.0000154913,0.0001619096,0.0001679736,0.0000778362],"domain_scores_gemma":[0.9997759,0.00005234183,0.00002297895,0.00003869041,0.0000924779,0.00001758748],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00053942,0.00017668,0.003699709,0.0001155896,0.0001312968,0.0002342981,0.00009529163,0.01582177,0.09867774,0.002073967,0.006588568,0.8718457],"study_design_scores_gemma":[0.00003972409,0.0003087803,0.01143887,0.00002791417,0.0001366535,0.001218935,0.00006361418,0.9078812,0.07138248,0.002484111,0.004963923,0.00005377756],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1651855,0.001914216,0.8194834,0.0004014402,0.0003835218,0.0002038256,0.0003392044,0.004073358,0.008015664],"genre_scores_gemma":[0.7951605,0.0008944007,0.1938025,0.0006021228,0.000219842,0.0001722058,0.0007595694,0.0001227401,0.008266231],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00367312,"threshold_uncertainty_score":0.008410692,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09400716326265252,"score_gpt":0.2929784460267927,"score_spread":0.1989712827641402,"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."}}