{"id":"W4404801468","doi":"10.1016/j.procs.2024.09.461","title":"Multi-Label Classification with Deep Learning and Manual Data Collection for Identifying Similar Bird Species","year":2024,"lang":"en","type":"article","venue":"Procedia Computer Science","topic":"Identification and Quantification in Food","field":"Biochemistry, Genetics and Molecular Biology","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Royal Military College of Canada","funders":"","keywords":"Computer science; Artificial intelligence; Data collection; Machine learning; Statistics","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":[0.002923076,0.001442845,0.001144061,0.00388462,0.001536749,0.001706468,0.003082057,0.00224162,0.003222565],"category_scores_gemma":[0.005935203,0.0005091868,0.001017322,0.002493031,0.001128514,0.003425854,0.002635109,0.002684848,0.002368646],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001696961,"about_ca_system_score_gemma":0.001492176,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007133867,"about_ca_topic_score_gemma":0.0200484,"domain_scores_codex":[0.9968727,0.0006550928,0.0002234417,0.001202661,0.0006773433,0.0003687398],"domain_scores_gemma":[0.9946243,0.001591403,0.0006754065,0.001561103,0.001301545,0.0002462376],"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":[0.0004828208,0.0008939416,0.02794882,0.0005281849,0.0001744987,0.0002869336,0.0005147647,0.03017988,0.02476713,0.00349059,0.01692229,0.8938101],"study_design_scores_gemma":[0.000044304,0.0002283488,0.01086837,0.0001228024,0.00006155837,0.0002705515,0.0006109322,0.9483548,0.01763215,0.01168336,0.01005595,0.00006689788],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2788166,0.001414311,0.6952279,0.001039647,0.0007834354,0.000878131,0.003302818,0.008070762,0.01046644],"genre_scores_gemma":[0.5578,0.0002333594,0.4281476,0.0006115472,0.0001598184,0.0004292595,0.00675626,0.0002890037,0.0055732],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007133867,"threshold_uncertainty_score":0.01545888,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1007911516650473,"score_gpt":0.355540649061696,"score_spread":0.2547494973966487,"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."}}