{"id":"W2969944961","doi":"10.1162/qss_a_00006","title":"Intellectual and social similarity among scholarly journals: An exploratory comparison of the networks of editors, authors and co-citations","year":2019,"lang":"en","type":"article","venue":"Quantitative Science Studies","topic":"Complex Network Analysis Techniques","field":"Physics and Astronomy","cited_by":28,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Montréal","funders":"","keywords":"Similarity (geometry); Citation; Field (mathematics); Association (psychology); Interlocking; Editorial board; Library science; Sociology; Social science; Computer science; Mathematics; Epistemology; Engineering; Artificial intelligence; Philosophy","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["bibliometrics"],"consensus_categories":[],"category_scores_codex":[0.002744435,0.0002517836,0.000366913,0.01371079,0.0007863576,0.002190332,0.0004229931,0.000461553,0.002199364],"category_scores_gemma":[0.01986296,0.0001591576,0.0004298413,0.01115998,0.001237528,0.002341062,0.001525369,0.0003272696,0.0002697169],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006486399,"about_ca_system_score_gemma":0.0005414957,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001506366,"about_ca_topic_score_gemma":0.001936062,"domain_scores_codex":[0.997348,0.001455802,0.0001574224,0.0002798414,0.0006303792,0.0001286012],"domain_scores_gemma":[0.9688135,0.0249619,0.003253615,0.000864819,0.001457871,0.000648387],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0006492109,0.0003293422,0.8186414,0.001540613,0.0008193392,0.0008124539,0.06595371,0.003864569,0.01232286,0.02122516,0.001577577,0.0722638],"study_design_scores_gemma":[0.00002521295,0.0003711715,0.9261243,0.0001211478,0.0001477209,0.00111501,0.04018613,0.01202309,0.002045178,0.01150409,0.006270936,0.00006600902],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9892238,0.0002921264,0.005266027,0.0001377396,0.00000712298,0.00007124736,0.001082672,0.00003983179,0.003879436],"genre_scores_gemma":[0.9950342,0.00009842381,0.0037657,0.0000113445,0.00001358288,0.00007000978,0.000710443,0.000009387479,0.0002867979],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9862892,"threshold_uncertainty_score":0.01451415,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1046701732834297,"score_gpt":0.4297293689054758,"score_spread":0.325059195622046,"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."}}