{"id":"W6892221294","doi":"10.5064/f6buax58/hxf2nh","title":"Burke_EDI_NENA.Codebook.2017.10.30.rtf","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":"Coding (social sciences); Codebook; Word processing; Word (group theory); File format","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":[0.004942847,0.001210375,0.001396182,0.005181013,0.001818817,0.004272665,0.004324107,0.001275292,0.4228869],"category_scores_gemma":[0.0525231,0.001313909,0.001048654,0.01169955,0.000718013,0.003641877,0.004278379,0.00249436,0.3160559],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003876948,"about_ca_system_score_gemma":0.008124144,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0314326,"about_ca_topic_score_gemma":0.05626958,"domain_scores_codex":[0.9973604,0.0008152628,0.0004441859,0.0004593259,0.000631828,0.0002889769],"domain_scores_gemma":[0.9817724,0.006555803,0.0007154854,0.003703739,0.006390306,0.000862312],"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":[0.00002265638,0.000009854474,0.0002339273,0.0005382776,0.0000068016,0.000004822256,0.0001210373,0.00005554045,0.00002351968,0.001070707,0.9935295,0.004383454],"study_design_scores_gemma":[0.00009462847,0.000008111151,0.001428727,0.0007401333,0.00001088135,0.00002014885,0.000396377,0.000116931,0.0001346022,0.002783786,0.9942416,0.00002418944],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001024028,0.00005822981,0.0005426282,0.0001605369,0.00005979939,0.0002404564,0.9924563,0.0004735999,0.005906084],"genre_scores_gemma":[0.00124783,0.0001942246,0.003325695,0.0001980772,0.00002348259,0.00642278,0.9770223,0.0007962861,0.01076935],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.4228869,"threshold_uncertainty_score":0.8231817,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1041887218085879,"score_gpt":0.3662551986255649,"score_spread":0.262066476816977,"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."}}