{"id":"W4394020713","doi":"10.5281/zenodo.3722784","title":"SpiegeLib: FM Sound Match Example Experiment","year":2020,"lang":"en","type":"dataset","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Music Technology and Sound Studies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"","keywords":"Sound (geography); Acoustics; Speech recognition; Computer science; Communication; Physics; Psychology","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":[0.001561776,0.003476453,0.00121102,0.001741773,0.001211913,0.001349551,0.003149747,0.002948503,0.03825799],"category_scores_gemma":[0.003839551,0.000539797,0.001699034,0.001880402,0.0006534788,0.001196948,0.002097317,0.002233155,0.05685394],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001486745,"about_ca_system_score_gemma":0.001227742,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01488114,"about_ca_topic_score_gemma":0.04287671,"domain_scores_codex":[0.9982654,0.0003436341,0.00014029,0.0005203545,0.0005483244,0.0001819687],"domain_scores_gemma":[0.9985568,0.000323391,0.00005934261,0.0005487454,0.0003750313,0.0001366343],"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":[0.0005436636,0.0003286756,0.001218182,0.0007283586,0.00009669094,0.0001445273,0.00004308602,0.001910405,0.001983767,0.0006365307,0.9730927,0.01927359],"study_design_scores_gemma":[0.001163697,0.0004241717,0.01477914,0.0002544869,0.0001507106,0.0008489233,0.0002477558,0.01454389,0.01036673,0.003487959,0.9535673,0.0001651385],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.01088488,0.0009359414,0.004839909,0.0005132856,0.0007283233,0.0004208203,0.9548952,0.01381826,0.01296348],"genre_scores_gemma":[0.005740233,0.00009370229,0.00463263,0.0002061106,0.00004308516,0.0003627873,0.9841829,0.0004248877,0.004313694],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.03825799,"threshold_uncertainty_score":0.1279857,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0582130601183989,"score_gpt":0.2608203055383061,"score_spread":0.2026072454199072,"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."}}