{"id":"W2152757094","doi":"10.1177/1094428107300202","title":"Deconstructing Scholarship","year":2007,"lang":"en","type":"article","venue":"Organizational Research Methods","topic":"scientometrics and bibliometrics research","field":"Decision Sciences","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Government of Alberta","keywords":"Structuring; Variety (cybernetics); Relevance (law); Scholarship; Craft; Citation; Selection (genetic algorithm); Tacit knowledge; Computer science; Citation analysis; Knowledge management; Data science; Sociology; Engineering ethics; Psychology; World Wide Web; Political science","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch","bibliometrics"],"consensus_categories":[],"category_scores_codex":[0.02589059,0.0009522975,0.0009262806,0.0135748,0.005370406,0.02230547,0.002272903,0.002332617,0.002346134],"category_scores_gemma":[0.0460347,0.0004929895,0.0006936002,0.009274736,0.05009108,0.02439566,0.01398772,0.003726174,0.0005569521],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.006852021,"about_ca_system_score_gemma":0.006193585,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002652103,"about_ca_topic_score_gemma":0.003429232,"domain_scores_codex":[0.9709784,0.02066268,0.001302316,0.001928183,0.004056172,0.001072188],"domain_scores_gemma":[0.948358,0.03536005,0.002645463,0.007911122,0.004531846,0.001193493],"domain_codex":null,"domain_gemma":"evaluation","domain_candidate":"evaluation","domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00001685234,0.00002217699,0.002532525,0.0001693256,0.00001319324,0.0001547132,0.06595095,0.0003937119,0.0003959465,0.9019212,0.0005245942,0.0279048],"study_design_scores_gemma":[0.000006077057,0.00001928246,0.001032365,0.0003445066,0.00001161166,0.000149103,0.03255029,0.001237798,0.0003786744,0.9284271,0.03583042,0.00001292917],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.3676664,0.01224093,0.3059211,0.03253223,0.0008369276,0.0004281437,0.0002866873,0.0005113311,0.2795762],"genre_scores_gemma":[0.9352889,0.002652591,0.05343958,0.0009774714,0.0002740846,0.0003614796,0.0001934652,0.0002048492,0.006607645],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9864252,"threshold_uncertainty_score":0.1369241,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.9114990024173193,"score_gpt":0.791205183478571,"score_spread":0.1202938189387482,"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."}}