{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch","metaepi_narrow","sts","scholarly_communication","open_science","insufficient_payload"],"consensus_categories":["scholarly_communication","insufficient_payload"],"category_scores_codex":[0.005593779,0.000419967,0.0006636514,0.0005497638,0.003055028,0.01045414,0.008983302,0.0003487072,0.008779576],"category_scores_gemma":[0.008663118,0.0003483653,0.0002719649,0.0005954841,0.0003298564,0.0647319,0.001128614,0.0006382134,0.01992576],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001244684,"about_ca_system_score_gemma":0.0002132525,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000257133,"about_ca_topic_score_gemma":0.001114773,"domain_scores_codex":[0.9932886,0.0003002808,0.001232158,0.001363272,0.003044125,0.0007715691],"domain_scores_gemma":[0.9939046,0.000732263,0.0008382237,0.002720395,0.0009979506,0.0008065925],"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":[0.0001232486,0.0001321526,0.003100486,0.000008449589,0.00003809838,0.0000575109,0.0002031918,0.0001155226,0.0004498142,0.1158317,0.8509369,0.02900293],"study_design_scores_gemma":[0.0008651896,0.0001164039,0.224363,0.0001024974,0.00002594416,0.00004490191,0.00036617,0.0001204327,0.002103407,0.03409842,0.7371814,0.0006123367],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.05644315,0.0001965537,0.01678921,0.458118,0.01503199,0.001352632,0.0008211826,0.0002908766,0.4509564],"genre_scores_gemma":[0.9268562,0.00005070541,0.001608051,0.04153313,0.002386084,0.0002380548,0.0001662116,0.00003799229,0.02712362],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.870413,"threshold_uncertainty_score":0.9998968,"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."}}