{"id":"W6912957099","doi":"10.5683/sp3/qdwa6l","title":"Absorption Data","year":2022,"lang":"en","type":"dataset","venue":"Borealis","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"","keywords":"Absorption (acoustics); Noise (video); Table (database); Data analysis; Feature (linguistics)","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":[0.001970672,0.003080743,0.001953365,0.004209116,0.001346185,0.002986163,0.003455326,0.002090169,0.1138645],"category_scores_gemma":[0.0086685,0.0008902704,0.001830948,0.007507898,0.0006400223,0.002009442,0.002083763,0.002318497,0.1783089],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001529861,"about_ca_system_score_gemma":0.0028734,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03395921,"about_ca_topic_score_gemma":0.05541373,"domain_scores_codex":[0.9977525,0.0003178192,0.0001874811,0.000690967,0.0007082364,0.0003430717],"domain_scores_gemma":[0.9957103,0.0008664419,0.0002354856,0.001327359,0.001526629,0.0003338662],"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":[0.0001154333,0.0000429051,0.0007216663,0.0004114194,0.00003021395,0.00001933121,0.00002554802,0.0002654823,0.0003310771,0.000400731,0.9945339,0.003102333],"study_design_scores_gemma":[0.0001670817,0.00003377897,0.004715333,0.0001456323,0.00005218927,0.00007398178,0.0001110319,0.0006106868,0.001177851,0.001497936,0.9913623,0.00005221182],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0002460736,0.00007293435,0.0002429986,0.00006216295,0.00005801434,0.00002395702,0.9948735,0.002329365,0.00209106],"genre_scores_gemma":[0.0007457683,0.00004394011,0.0006309389,0.00006811356,0.00001317621,0.00007001021,0.9967033,0.0004481853,0.001276578],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1138645,"threshold_uncertainty_score":0.3809147,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06579090088347586,"score_gpt":0.3200028610753762,"score_spread":0.2542119601919003,"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."}}