{"id":"W1998047186","doi":"10.1016/j.serrev.2009.08.017","title":"The 5K Run Toolkit: A Quick, Painless, and Thoughtful Approach to Managing Print Journal Backruns","year":2009,"lang":"en","type":"article","venue":"Serials Review","topic":"Library Collection Development and Digital Resources","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Computer science; World Wide Web; Subject (documents); Identification (biology); Collection development; Resolver; Open source; Academic library; Data science; Information retrieval; Library science; Operating system; Telecommunications; Software","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.02958464,0.002175972,0.001773577,0.008176444,0.003864272,0.01896353,0.006143587,0.002516591,0.07761462],"category_scores_gemma":[0.1111552,0.003376521,0.001236143,0.00388577,0.003452153,0.01695945,0.01034079,0.006937646,0.09141961],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002219291,"about_ca_system_score_gemma":0.01253989,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005624451,"about_ca_topic_score_gemma":0.01431102,"domain_scores_codex":[0.9686817,0.008228399,0.003159466,0.001971729,0.01660572,0.00135295],"domain_scores_gemma":[0.8585392,0.03874297,0.006476101,0.03326285,0.05042456,0.01255432],"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":[0.0001588389,0.0001259286,0.0008035989,0.0003453068,0.00003573479,0.000244904,0.001639647,0.0002265773,0.002673314,0.004122158,0.6611032,0.3285208],"study_design_scores_gemma":[0.00009595112,0.0001059017,0.001430461,0.0005274031,0.00005255847,0.0006536216,0.00113605,0.002226186,0.003116594,0.00579982,0.9846206,0.0002349168],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"software","genre_gemma":"methods","genre_scores_codex":[0.004548083,0.00187834,0.3592443,0.01580655,0.005356218,0.001895945,0.002833747,0.5315154,0.07692147],"genre_scores_gemma":[0.03185645,0.002704588,0.571155,0.006554752,0.00289555,0.001425211,0.006512332,0.1414922,0.235404],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.07761462,"threshold_uncertainty_score":0.2596468,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01760627152858407,"score_gpt":0.2404821478691715,"score_spread":0.2228758763405875,"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."}}