{"id":"W6925590825","doi":"10.17882/101899","title":"Deep-sea observatories images labeled by citizen for object detection algorithms","year":2024,"lang":"en","type":"dataset","venue":"SEANOE","topic":"Fetal and Pediatric Neurological Disorders","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"HORIZON EUROPE Framework Programme; Seventh Framework Programme","keywords":"Citizen science; Annotation; Directory; Object detection; Hyperspectral imaging; Underwater; Class (philosophy); Object (grammar)","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005939948,0.001335912,0.0006818225,0.003473322,0.0009485038,0.0009947469,0.001220669,0.001436836,0.007507272],"category_scores_gemma":[0.001711263,0.0005132024,0.00115398,0.003179526,0.0005523649,0.001162562,0.001540543,0.001141267,0.01141022],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001201723,"about_ca_system_score_gemma":0.00144173,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04099425,"about_ca_topic_score_gemma":0.0875274,"domain_scores_codex":[0.9985941,0.00007485916,0.00009425508,0.0005766142,0.000362299,0.0002979014],"domain_scores_gemma":[0.9986573,0.00008906033,0.0001312052,0.0005210305,0.0005042335,0.00009707355],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001586162,0.0007530915,0.04348985,0.002669133,0.0003215817,0.001376516,0.001246316,0.008293481,0.04595613,0.001594952,0.631442,0.2612708],"study_design_scores_gemma":[0.0002004651,0.0003358208,0.1928129,0.000793752,0.0002098869,0.001253539,0.002874849,0.04373437,0.05338295,0.002259799,0.7019386,0.0002030491],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.1316899,0.001257041,0.0170933,0.0004939697,0.0004705149,0.0006733702,0.810127,0.02071539,0.01747947],"genre_scores_gemma":[0.05761024,0.0002759815,0.02252739,0.0001130579,0.00004144461,0.0002502141,0.9139985,0.0006350065,0.004548092],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.04099425,"threshold_uncertainty_score":0.08151126,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01492274557837329,"score_gpt":0.2702755471954576,"score_spread":0.2553528016170843,"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."}}