{"id":"W68533599","doi":"10.7771/2380-176x.2426","title":"I Hear the Train A Comin' -- pub2web and MetaStore","year":2008,"lang":"en","type":"article","venue":"Against the grain","topic":"Research Data Management Practices","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Nexen (Canada)","funders":"","keywords":"Computer science; Telecommunications","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":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.008223628,0.0005572758,0.0008282185,0.001948133,0.007042459,0.01003423,0.001312612,0.01468212,0.152206],"category_scores_gemma":[0.03216063,0.0007112476,0.0006460724,0.001625585,0.003105378,0.01006254,0.005891035,0.01541327,0.05725175],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002811936,"about_ca_system_score_gemma":0.003466978,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008969138,"about_ca_topic_score_gemma":0.02426845,"domain_scores_codex":[0.9967324,0.001006649,0.0001822352,0.0003443596,0.00120547,0.0005289388],"domain_scores_gemma":[0.9708136,0.01644952,0.001067418,0.00195184,0.003680171,0.006037439],"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":[0.00002309336,0.000008407919,0.0002385402,0.0000192475,0.000002418677,0.00006987059,0.0002565288,0.000004303672,0.00009115876,0.002970478,0.9911834,0.005132578],"study_design_scores_gemma":[0.00001157447,0.00001068066,0.000383091,0.00004753897,0.000003386024,0.00007862947,0.0008442551,0.00003682745,0.00008050332,0.001797806,0.9966941,0.00001163447],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"software","genre_scores_codex":[0.001099799,0.001334876,0.001918829,0.8771727,0.05977169,0.00005340716,0.000841116,0.001128443,0.05667907],"genre_scores_gemma":[0.007922918,0.0005885483,0.001226872,0.492646,0.01562907,0.00006349137,0.0003481217,0.0009020251,0.480673],"genre_candidate":"software","genre_consensus":null,"teacher_disagreement_score":0.9899657,"threshold_uncertainty_score":0.5091797,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.102982365564896,"score_gpt":0.308131626446318,"score_spread":0.205149260881422,"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."}}