{"id":"W4383184463","doi":"10.5281/zenodo.8107968","title":"Linking Epic Speeches","year":2023,"lang":"en","type":"paratext","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Digital Humanities and Scholarship","field":"Arts and Humanities","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Mount Allison University","funders":"","keywords":"EPIC; Computer science; Art; Literature","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":["metaepi_narrow","sts","scholarly_communication","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.000602815,0.0003200833,0.0003271681,0.0004516746,0.004575092,0.008447158,0.00156727,0.0001506433,0.3229395],"category_scores_gemma":[0.000233859,0.000328999,0.0001621205,0.0001595293,0.0004199166,0.0005373782,0.001466479,0.0007950255,0.4477356],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001701392,"about_ca_system_score_gemma":0.000006977239,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003881317,"about_ca_topic_score_gemma":0.000005869237,"domain_scores_codex":[0.9977071,0.0002138223,0.0004038406,0.0005624684,0.000530761,0.0005819873],"domain_scores_gemma":[0.9983857,0.00005381034,0.0001984605,0.0005463331,0.0006507022,0.0001650357],"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":[0.00001518061,0.0000474422,3.178068e-8,0.000203602,0.00006431091,0.00001949066,0.005685559,0.000006150693,0.000008546604,0.05391005,0.9022432,0.03779645],"study_design_scores_gemma":[0.0001843745,0.0001632577,0.000003438601,0.0002277167,0.00002303977,0.00001965766,0.001835507,0.00001090006,0.00001490204,0.001391901,0.9957495,0.000375828],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.0005767012,0.0003150367,0.00002416954,0.000290158,0.001786596,0.0003552485,0.001768349,0.001106202,0.9937775],"genre_scores_gemma":[0.02656811,0.0003530502,0.00001376,0.0002880001,0.003509356,7.79749e-8,0.01905405,0.004566934,0.9456466],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.1247961,"threshold_uncertainty_score":0.9999162,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1224891210483331,"score_gpt":0.2614959891061893,"score_spread":0.1390068680578562,"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."}}