{"id":"W4233477786","doi":"10.1163/37667_dupr_dupr-25","title":"NVL-ECH-SLN (Winnipeg): correspondence of ir. R.P. Dojes to SLN about a.o. Holla…","year":2020,"lang":"en","type":"dataset","venue":"Transatlantic Relations Online : Digital Archives of the Roosevelt Institute for American Studies","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Speech recognition; Computer science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","sts"],"consensus_categories":[],"category_scores_codex":[0.0002329446,0.001272451,0.002925222,0.001042156,0.0005497899,0.00009287454,0.002907446,0.0001579464,0.000008408854],"category_scores_gemma":[0.003102912,0.0009700237,0.001427238,0.002596112,0.007005705,0.0005761939,0.0008034499,0.0009204503,0.0002196597],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001303883,"about_ca_system_score_gemma":0.0008750636,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005726712,"about_ca_topic_score_gemma":0.001839748,"domain_scores_codex":[0.9940001,0.0001950537,0.002437526,0.001246611,0.001214735,0.0009059408],"domain_scores_gemma":[0.9929143,0.002418022,0.002063424,0.001839025,0.0004355144,0.0003297247],"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":[0.002252989,0.001374035,0.000607338,0.001648315,0.004186292,0.00001921413,0.003554891,0.0119769,0.0003290271,0.0003072401,0.9634295,0.01031431],"study_design_scores_gemma":[0.001478052,0.001099487,0.008837181,0.002879673,0.001808913,0.00003355058,0.001632243,0.0002697298,0.0001544631,0.0007774808,0.9797052,0.001324084],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0093766,0.000960255,0.003956508,0.001743951,0.0007678531,0.002975707,0.9797667,0.0001539197,0.0002984778],"genre_scores_gemma":[0.05013246,0.001719741,0.01363528,0.000244139,0.0004438148,0.0003396927,0.9318829,0.0002442822,0.001357724],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.04788387,"threshold_uncertainty_score":0.999275,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03735008707417375,"score_gpt":0.3246602686552426,"score_spread":0.2873101815810689,"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."}}