{"id":"W7064971536","doi":"","title":"Deep Learning Applied to Animal Linguistics","year":2023,"lang":"en","type":"dissertation","venue":"","topic":"Particle Detector Development and Performance","field":"Physics and Astronomy","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Scope (computer science); Deep learning; Variety (cybernetics); Process (computing); Animal behavior; Repertoire; Field (mathematics); Natural (archaeology)","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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00005643973,0.0001498629,0.0001505606,0.00006956268,0.0001076049,0.00004684297,0.0001000796,0.00004969711,0.0008254251],"category_scores_gemma":[0.00001518619,0.0001515429,0.00003957903,0.0001812761,0.000002859078,0.00000848577,0.00001799378,0.0002068342,0.002724211],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001091068,"about_ca_system_score_gemma":0.00003512775,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003479117,"about_ca_topic_score_gemma":0.00004675493,"domain_scores_codex":[0.999297,0.000004337856,0.0001618365,0.0001885954,0.0001261172,0.0002221623],"domain_scores_gemma":[0.9997039,0.00002415991,0.0000547277,0.00008027041,0.0000653772,0.00007151366],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.001137354,0.0002408102,0.1705563,0.0005389843,0.001024286,0.00001429486,0.0287333,0.00555574,0.03431911,0.08815781,0.02337158,0.6463504],"study_design_scores_gemma":[0.001516355,0.0003270202,0.4580679,0.0002802776,0.0002477485,1.341352e-7,0.01689567,0.01697498,0.1963336,0.002435853,0.3029701,0.003950368],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6785938,0.000004555297,0.000171749,0.000002279742,0.0006852302,0.0001366847,0.000001760976,0.0001267558,0.3202772],"genre_scores_gemma":[0.9560532,8.991364e-7,0.0004021705,0.000009779813,0.0007415474,0.00005226869,0.0006407849,0.00003732265,0.04206206],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6424001,"threshold_uncertainty_score":0.9980523,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01225088744046851,"score_gpt":0.2675134749877318,"score_spread":0.2552625875472633,"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."}}