{"id":"W7144169336","doi":"10.20736/0002001136","title":"第3回 SPARC Japan セミナー2013 「オープンアクセス時代の研究成果のインパクトを再定義する：再利用とAltmetricsの現在」 ディスカッション　ドキュメント","year":2013,"lang":"ja","type":"article","venue":"Institutional Repositories DataBase (IRDB)","topic":"Military Technology and Strategies","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Impact; OpenAlex","funders":"","keywords":"Line (geometry); Feature (linguistics); Margin (machine learning)","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":["metaepi_narrow","sts","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0005209299,0.001178129,0.0009902436,0.0008901656,0.001517711,0.00057983,0.001406919,0.001005705,0.001779186],"category_scores_gemma":[0.001008421,0.001227944,0.0003741326,0.00187423,0.001661113,0.003754807,0.0006505184,0.001861347,0.003677035],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007747622,"about_ca_system_score_gemma":0.0007684577,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004819513,"about_ca_topic_score_gemma":0.0003112881,"domain_scores_codex":[0.9940178,0.000158583,0.001580971,0.001402078,0.001297144,0.001543401],"domain_scores_gemma":[0.995668,0.0004982258,0.0002799745,0.002223746,0.0007002026,0.0006298455],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001695692,0.0008176098,0.01092443,0.001539768,0.001448271,0.0009491532,0.001094633,0.007538026,0.01972547,0.8334775,0.1172682,0.005047419],"study_design_scores_gemma":[0.006273508,0.001473147,0.07101202,0.003532688,0.001353946,0.003969637,0.00642329,0.02928839,0.03457316,0.03446499,0.7982533,0.009381953],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6641415,0.03515862,0.01219008,0.002872729,0.03169094,0.003155458,0.004226528,0.003922245,0.2426418],"genre_scores_gemma":[0.9828491,0.001971956,0.007726367,0.0001806118,0.002533818,0.0003324017,0.001600177,0.0001138661,0.002691742],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7990125,"threshold_uncertainty_score":0.9997822,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01442429764418349,"score_gpt":0.2228935435893067,"score_spread":0.2084692459451232,"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."}}