{"id":"W2187881876","doi":"10.17723/aarc.73.2.00101k28200838k4","title":"The Development, Testing, and Evaluation of the Archival Metrics Toolkits","year":2010,"lang":"en","type":"article","venue":"The American Archivist","topic":"Digital and Traditional Archives Management","field":"Arts and Humanities","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; Library and Archives Canada","funders":"","keywords":"Computer science","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":[],"consensus_categories":[],"category_scores_codex":[0.0005691666,0.00008813904,0.0000843534,0.00003889446,0.0008004986,0.0001579797,0.0003902357,6.088399e-7,0.00000298367],"category_scores_gemma":[0.0002754127,0.00003842236,0.00003946332,0.00009379362,0.002179025,0.0000527702,0.0002045745,0.0001510305,0.00001011515],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000005513689,"about_ca_system_score_gemma":0.00006092727,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000931635,"about_ca_topic_score_gemma":0.0003545593,"domain_scores_codex":[0.9990532,0.0001010005,0.0001705912,0.0001135516,0.0004142967,0.0001473987],"domain_scores_gemma":[0.9985095,0.0009727924,0.0001890503,0.0002411986,0.00005813313,0.00002930874],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.000009700728,0.00003392013,0.0002488679,0.000004953687,0.00003675281,8.348216e-8,0.002441815,0.000006385701,0.00007826613,0.122784,0.0003780055,0.8739773],"study_design_scores_gemma":[0.00006683069,0.00003829994,0.9150488,0.000008819767,0.00003422083,0.000002110624,0.0001412531,0.000679252,0.00004201934,0.04772862,0.0361397,0.00007002046],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.694496,0.000001611557,0.00001130088,0.0007134281,0.0001182784,0.000161303,0.00001373883,0.00001105179,0.3044733],"genre_scores_gemma":[0.9977513,0.000003618079,0.000284146,0.0001827914,0.0001344293,0.00002736957,0.000003652094,0.000008047879,0.001604643],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9148,"threshold_uncertainty_score":0.8028707,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0568721882165615,"score_gpt":0.2518866652112255,"score_spread":0.195014476994664,"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."}}