{"id":"W6899128392","doi":"10.58079/o8aa","title":"Welcome to #EMROCTranscribes 2017!","year":2017,"lang":"en","type":"article","venue":"OpenEdition (OpenEdition)","topic":"Academic Publishing and Open Access","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Government (linguistics); Work (physics); Context (archaeology); Focus (optics)","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0009175609,0.0006041912,0.0004089337,0.00108873,0.002134163,0.00690668,0.000996404,0.001517824,0.7639898],"category_scores_gemma":[0.007223693,0.0003356037,0.0004436418,0.001035735,0.0008151896,0.00414396,0.003461645,0.00242725,0.7110307],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001171871,"about_ca_system_score_gemma":0.001446568,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003596561,"about_ca_topic_score_gemma":0.009903303,"domain_scores_codex":[0.999249,0.0001195484,0.00002964348,0.00009412497,0.0004060837,0.0001015374],"domain_scores_gemma":[0.9965813,0.0005374468,0.00009717588,0.0003696545,0.001318563,0.001095851],"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":[0.00001564637,0.000006993327,0.00002159438,0.00002576056,5.469204e-7,0.00002906748,0.00004506956,0.000008120421,0.00009636044,0.001145683,0.9787745,0.01983057],"study_design_scores_gemma":[0.000001451264,0.000003247759,0.00004011938,0.00001529595,2.744818e-7,0.00001597978,0.00006689417,0.00001149227,0.00006107314,0.0001917094,0.9995895,0.000002928493],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.000850016,0.001350188,0.003422293,0.01591259,0.02880105,0.0001686613,0.005235893,0.007647478,0.9366118],"genre_scores_gemma":[0.001145834,0.0003625082,0.0005365472,0.001623181,0.0007232395,0.00003968634,0.001218695,0.001851239,0.9924991],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.7639898,"threshold_uncertainty_score":0.3366399,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09885991120484335,"score_gpt":0.3857924477389715,"score_spread":0.2869325365341281,"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."}}