{"id":"W6931631420","doi":"10.5281/zenodo.7789270","title":"Source Codes- A Vocalization-Processing Network in Marmosets","year":2023,"lang":"en","type":"other","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Circadian rhythm and melatonin","field":"Neuroscience","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"","keywords":"Artificial neural network; Feature (linguistics); Set (abstract data type); Noise (video); Key (lock)","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0005191863,0.001448563,0.0005753192,0.002272219,0.0006670474,0.001493515,0.001255112,0.001729696,0.3399419],"category_scores_gemma":[0.01090737,0.0003857156,0.0006589944,0.003298352,0.0005441305,0.001063718,0.001533892,0.001079134,0.05350428],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005368668,"about_ca_system_score_gemma":0.0009000834,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005360888,"about_ca_topic_score_gemma":0.003889338,"domain_scores_codex":[0.9995918,0.00005134648,0.00005764985,0.00008441151,0.0001641148,0.00005073032],"domain_scores_gemma":[0.9952338,0.002344642,0.000338366,0.0005315227,0.001386965,0.0001647401],"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":[0.0009788634,0.00007996754,0.002785358,0.00199875,0.00006109995,0.0005096905,0.0004360032,0.002175584,0.01063533,0.01684814,0.8569209,0.1065703],"study_design_scores_gemma":[0.0006804604,0.0001591188,0.02855089,0.001019597,0.00008862732,0.002732207,0.0003708701,0.01737742,0.02474048,0.0620009,0.8620732,0.0002061714],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"other","genre_scores_codex":[0.01885456,0.000958016,0.08465961,0.003982875,0.004763588,0.0005699148,0.7828599,0.02572871,0.07762281],"genre_scores_gemma":[0.1823537,0.001438001,0.1654435,0.001830917,0.001603799,0.003733925,0.4784295,0.03097505,0.1341916],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.3399419,"threshold_uncertainty_score":0.9414927,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04083200334658196,"score_gpt":0.2606940862305559,"score_spread":0.2198620828839739,"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."}}