{"id":"W4393091763","doi":"10.23977/acss.2024.080117","title":"Research on Largemouth Bass Target Recognition and Tracking Utilizing the Optical Flow Approach","year":2024,"lang":"en","type":"article","venue":"Advances in Computer Signals and Systems","topic":"Water Quality Monitoring Technologies","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Bass (fish); Optical flow; Tracking (education); Computer science; Artificial intelligence; Fishery; Computer vision; Environmental science; Biology; Psychology; Image (mathematics)","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002072981,0.0001059784,0.0001396618,0.00007454028,0.0001479204,0.0003122712,0.0001806679,0.00006987215,0.000004090588],"category_scores_gemma":[0.00002231567,0.00006880231,0.00001688066,0.0002527959,0.0002288184,0.000331023,0.0002389966,0.0003387545,0.00002298717],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005451976,"about_ca_system_score_gemma":0.000002964127,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004886306,"about_ca_topic_score_gemma":0.000003117162,"domain_scores_codex":[0.9985349,0.0002596495,0.0002020994,0.0004079991,0.0003243784,0.000270996],"domain_scores_gemma":[0.9992387,0.0005354694,0.00001910076,0.0001643033,0.000008240746,0.00003421124],"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":[0.00003654552,0.0001335112,0.009954711,0.0007040583,0.00002871851,0.00008812106,0.004353741,0.06954809,0.001103143,0.003747751,0.0006364738,0.9096651],"study_design_scores_gemma":[0.0002781909,0.0003316222,0.003560163,0.001194358,0.000007399562,0.00006645836,0.003722877,0.960464,0.002723834,0.01761528,0.009640967,0.000394847],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8497183,0.01325996,0.1300117,0.0007006582,0.001354944,0.000832632,0.00001793373,0.0003180739,0.003785712],"genre_scores_gemma":[0.9904007,0.0002676357,0.009079192,0.00001620035,0.0001637928,0.00004294349,0.0000026263,0.000009838049,0.00001709364],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9092703,"threshold_uncertainty_score":0.3011239,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1510318706483506,"score_gpt":0.3499706971864862,"score_spread":0.1989388265381357,"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."}}