{"id":"W2084110111","doi":"10.1109/crv.2014.35","title":"Computer Vision-Based Identification of Individual Turtles Using Characteristic Patterns of Their Plastrons","year":2014,"lang":"en","type":"article","venue":"","topic":"Turtle Biology and Conservation","field":"Environmental Science","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"","keywords":"Turtle (robot); Artificial intelligence; Identification (biology); Computer science; Computer vision; Identity (music); Artificial neural network; Pattern recognition (psychology); Image processing; Image (mathematics); Feature (linguistics); Feature extraction; Visualization; Point (geometry); Mathematics; Biology; Ecology","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":[0.0002940275,0.0003261938,0.0002802991,0.001104432,0.0001244668,0.0004604997,0.0003532402,0.0003879646,0.0007857576],"category_scores_gemma":[0.0008452229,0.0001625509,0.0003058025,0.0005296208,0.0003824601,0.0005155538,0.0003279896,0.0003114702,0.0003468584],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002014758,"about_ca_system_score_gemma":0.00018836,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001220512,"about_ca_topic_score_gemma":0.001738005,"domain_scores_codex":[0.9998541,0.00002095668,0.000007693402,0.00006301027,0.00003613448,0.0000180941],"domain_scores_gemma":[0.999691,0.00009093976,0.00005676447,0.00004907245,0.00009507483,0.00001720244],"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":[0.0003451786,0.0001375706,0.01134645,0.0002054732,0.0000608416,0.0002280608,0.0001605678,0.05869593,0.316213,0.001568551,0.001248408,0.6097899],"study_design_scores_gemma":[0.00001468103,0.0001794774,0.04423118,0.00003427971,0.00006384078,0.0008180056,0.0001480478,0.8325322,0.1174307,0.002302404,0.00221197,0.00003329396],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1964398,0.0003873289,0.8001536,0.0001017183,0.00002885499,0.00007757632,0.0001428933,0.0009731489,0.001695028],"genre_scores_gemma":[0.7680789,0.0003293976,0.2296939,0.00005056267,0.00001982044,0.00004752864,0.0002698941,0.00004103301,0.001468947],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001220512,"threshold_uncertainty_score":0.002628684,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01295100437968448,"score_gpt":0.2239390017530847,"score_spread":0.2109879973734002,"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."}}