{"id":"W2769097657","doi":"10.1080/19186444.2009.11658213","title":"The Thomson Reuters Journal Selection Process","year":2009,"lang":"en","type":"article","venue":"Transnational Corporation Review","topic":"Media Studies and Communication","field":"Social Sciences","cited_by":157,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Selection (genetic algorithm); Process (computing); Economics; Computer science; Artificial intelligence","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.05360134,0.0007679376,0.003011145,0.02508447,0.003819905,0.01038708,0.001639378,0.00264614,0.04368955],"category_scores_gemma":[0.2574469,0.001021944,0.001214382,0.0220274,0.001932749,0.003676919,0.004493605,0.003002201,0.04635533],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002419481,"about_ca_system_score_gemma":0.01653553,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002640415,"about_ca_topic_score_gemma":0.003627117,"domain_scores_codex":[0.9487879,0.01750094,0.005617727,0.002725037,0.02351371,0.001854531],"domain_scores_gemma":[0.7421619,0.1083419,0.01290226,0.02746021,0.09912439,0.0100094],"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":[0.000612791,0.0001779612,0.004044484,0.00116473,0.0001412469,0.0004924505,0.001074532,0.0004581124,0.002295146,0.02973567,0.6265332,0.3332697],"study_design_scores_gemma":[0.0003927829,0.000175787,0.01434211,0.001034998,0.0001866097,0.0005266864,0.0009336474,0.005141319,0.003093987,0.05051841,0.9234996,0.0001540064],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.09755862,0.02104891,0.2028865,0.1322273,0.03214635,0.0457102,0.05784981,0.008186437,0.4023859],"genre_scores_gemma":[0.2106308,0.01647314,0.2631518,0.01147796,0.01818743,0.04063395,0.04464062,0.004418246,0.3903862],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9896129,"threshold_uncertainty_score":0.2834744,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05150941295268005,"score_gpt":0.3701919150226212,"score_spread":0.3186825020699411,"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."}}