{"id":"W1516388499","doi":"10.1108/02640470710729083","title":"Federal Science eLibrary Pilot","year":2007,"lang":"en","type":"article","venue":"The Electronic Library","topic":"scientometrics and bibliometrics research","field":"Decision Sciences","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"National Research Council Canada","funders":"","keywords":"Government (linguistics); Work (physics); Originality; Alliance; Computer science; Public relations; Library science; Business; World Wide Web; Political science; Engineering","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":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch","bibliometrics","scholarly_communication","open_science","insufficient_payload"],"consensus_categories":["bibliometrics","insufficient_payload"],"category_scores_codex":[0.03046434,0.0001732372,0.000211065,0.02330044,0.001133932,0.005014094,0.007781673,0.00005403546,0.002214999],"category_scores_gemma":[0.004568093,0.00009180381,0.0001157899,0.2018258,0.0009480509,0.004736885,0.001827107,0.0006433171,0.001047939],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001156685,"about_ca_system_score_gemma":0.00179232,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001730624,"about_ca_topic_score_gemma":0.000004046911,"domain_scores_codex":[0.9878342,0.0001683431,0.0006147898,0.0007889559,0.008537134,0.002056557],"domain_scores_gemma":[0.9937481,0.003942195,0.0001748686,0.001295503,0.0003402982,0.0004990431],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0003406319,0.0003400355,0.06626178,0.000003471551,0.00002626233,0.0000430396,0.0002328356,0.00001584764,0.01136655,0.5105817,0.1414997,0.2692882],"study_design_scores_gemma":[0.0006856179,0.001010445,0.1892131,0.000005666075,0.000003951162,0.00006725947,0.0003368382,0.001547138,0.05229324,0.5013148,0.2530999,0.0004219983],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7638259,0.003333379,0.00233539,0.008959292,0.0006306723,0.0003559456,0.000005567555,0.0001846428,0.2203692],"genre_scores_gemma":[0.9828894,0.0001787869,0.0002648864,0.001801727,0.000315106,0.000004497092,0.00000213118,0.00002094653,0.01452251],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2688662,"threshold_uncertainty_score":0.9997299,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3907233330194798,"score_gpt":0.5276591830770152,"score_spread":0.1369358500575354,"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."}}