{"id":"W4323343597","doi":"10.5860/crln.84.3.123","title":"Library publishing workflows: Three big lessons learned from cohort-based documentation","year":2023,"lang":"en","type":"article","venue":"College & Research Libraries News","topic":"Research Data Management Practices","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Brandon University","funders":"Institute of Museum and Library Services","keywords":"Publishing; Workflow; Metadata; Documentation; World Wide Web; Computer science; Library science; Scholarly communication; Political science; Database","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","sts","scholarly_communication","open_science","insufficient_payload"],"consensus_categories":["scholarly_communication","open_science"],"category_scores_codex":[0.004379145,0.0003307748,0.0003850978,0.002082193,0.001319496,0.06424078,0.009098719,0.0002061181,0.0005978722],"category_scores_gemma":[0.005246722,0.0003183977,0.0001338431,0.01111236,0.0004830134,0.195477,0.008300642,0.001469665,0.001095092],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000128105,"about_ca_system_score_gemma":0.001979141,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001371683,"about_ca_topic_score_gemma":0.0005117416,"domain_scores_codex":[0.9905078,0.002014761,0.0006119962,0.001708881,0.003468843,0.001687686],"domain_scores_gemma":[0.9892306,0.006536878,0.0002116507,0.003184294,0.0002213893,0.0006151958],"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":[0.0001533817,0.00009774452,0.009585305,0.00004692443,0.0001058409,0.0004104754,0.0001786477,0.0001216287,0.0001420307,0.3701867,0.5252937,0.09367767],"study_design_scores_gemma":[0.001285501,0.0001834427,0.01883374,0.0001115077,0.00001107623,8.898492e-7,0.001095224,0.04257736,0.001364297,0.1509814,0.7831036,0.000451935],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.01996627,0.001194978,0.1682754,0.6857328,0.001635996,0.003969243,0.0008771702,0.004370517,0.1139776],"genre_scores_gemma":[0.374246,0.0202503,0.3265194,0.01355163,0.006161513,0.00680368,0.0139261,0.0009385421,0.2376028],"genre_candidate":"commentary","genre_consensus":null,"teacher_disagreement_score":0.6721811,"threshold_uncertainty_score":0.9999806,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3341429007871973,"score_gpt":0.4091827522226307,"score_spread":0.0750398514354334,"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."}}