{"id":"W6948299441","doi":"10.5064/f6buax58/l1ypsr","title":"Burke_EDI_NENA.initiatives.2017.10.10.ods","year":2018,"lang":"en","type":"dataset","venue":"Syracuse University Qualitative Data Repository","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Workbook; Microsoft excel; Base (topology); Set (abstract data type); Data set; Column (typography)","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.002121564,0.0009455943,0.0009214972,0.004776292,0.001183899,0.003335364,0.002148636,0.0009608672,0.2170507],"category_scores_gemma":[0.01415421,0.0008846557,0.000692479,0.009261842,0.0004355909,0.002266872,0.003145286,0.00159649,0.2091749],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00197436,"about_ca_system_score_gemma":0.004101047,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03788451,"about_ca_topic_score_gemma":0.05867698,"domain_scores_codex":[0.9987218,0.0003349277,0.0001542941,0.0002608395,0.0003115856,0.0002165258],"domain_scores_gemma":[0.9952313,0.001340983,0.0004092786,0.001369313,0.001186163,0.0004628784],"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":[0.00002906944,0.00001234559,0.0008542793,0.0004076223,0.000008652724,0.00001037994,0.00009841756,0.00007286287,0.00003525616,0.001077383,0.9926576,0.004736058],"study_design_scores_gemma":[0.00004844921,0.0000069188,0.002779033,0.0003576087,0.000006573774,0.00001968922,0.0002884711,0.0001011992,0.0001483295,0.0009674396,0.9952604,0.00001596519],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001375596,0.00003776633,0.0001192706,0.0001135041,0.00003188306,0.0000242011,0.9960937,0.0002397944,0.003202351],"genre_scores_gemma":[0.0009268431,0.00011286,0.0008982929,0.00008533574,0.00001465343,0.0006289564,0.9910948,0.0002496026,0.005988591],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.7829493,"threshold_uncertainty_score":0.726107,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.104985441703391,"score_gpt":0.3764806245429016,"score_spread":0.2714951828395106,"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."}}