{"id":"W4393571495","doi":"10.5281/zenodo.4660053","title":"Pitch contours from subset of Intonational Bestiary","year":2021,"lang":"en","type":"dataset","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Archaeological Research and Protection","field":"Earth and Planetary Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Bestiary; Linguistics; Computer science; Art; Literature; Philosophy","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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0007698919,0.0001864705,0.0002693791,0.0002369782,0.001064637,0.0002578103,0.001211703,0.0002091139,0.2068268],"category_scores_gemma":[0.002099283,0.0001749067,0.00008789029,0.0004752177,0.0003918979,0.0001775413,0.0005295882,0.0006882148,0.00599088],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002845132,"about_ca_system_score_gemma":0.00002044828,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002515015,"about_ca_topic_score_gemma":0.0001117621,"domain_scores_codex":[0.9971921,0.0007532314,0.0003350191,0.000502041,0.0008389272,0.0003786447],"domain_scores_gemma":[0.9982812,0.0002010731,0.000186873,0.0004465747,0.000617308,0.0002669732],"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":[0.000101137,0.00003163639,0.00001703358,0.00005854021,0.00005514805,0.00003696874,0.0000485484,0.00005813022,0.00003835071,0.00002720785,0.9196402,0.07988706],"study_design_scores_gemma":[0.0002404701,0.0003033045,0.004719677,0.00005265209,0.00001748449,0.00003190612,0.00007988109,0.0001239741,0.00006002522,0.001400544,0.9927918,0.0001783335],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.001183269,0.0005433348,0.0004839856,0.0003222395,0.0001540905,0.0003252303,0.9920546,0.000107578,0.004825675],"genre_scores_gemma":[0.006275773,0.0006956409,0.0003098438,0.00009480517,0.0002665142,2.134789e-8,0.9921434,0.0001130013,0.0001010099],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.2008359,"threshold_uncertainty_score":0.994783,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03783107477670111,"score_gpt":0.2384975585646944,"score_spread":0.2006664837879933,"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."}}