{"id":"W4400101542","doi":"10.56294/piii2024272","title":"Contributions of bibliometrics to the study of interdiscipline. A methodology for the analysis of the intersection between the fields of neurosciences and computational sciences","year":2024,"lang":"en","type":"article","venue":"SCT Proceedings in Interdisciplinary Insights and Innovations.","topic":"Psychology Research and Bibliometrics","field":"Psychology","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"","keywords":"Bibliometrics; Intersection (aeronautics); Computer science; Management science; Library science; Geography; Engineering; Cartography","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":["bibliometrics"],"consensus_categories":[],"category_scores_codex":[0.003333034,0.0001015642,0.0003068816,0.01096494,0.000392304,0.00006595701,0.0006539631,0.00006951148,0.00000932542],"category_scores_gemma":[0.0008805855,0.0000422174,0.00008691422,0.08206116,0.001336893,0.0001611805,0.0008566356,0.0002651454,1.007299e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001481168,"about_ca_system_score_gemma":0.00004974782,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007074938,"about_ca_topic_score_gemma":0.00009813491,"domain_scores_codex":[0.9983841,0.0001242692,0.0007145501,0.0002945908,0.0003237051,0.000158803],"domain_scores_gemma":[0.995182,0.003632585,0.0003034545,0.0001597959,0.0007017119,0.00002043392],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0007317444,0.001677532,0.451227,0.0003684336,0.003768619,0.000001265257,0.1897966,0.001501269,0.005062504,0.2737014,0.01268932,0.05947428],"study_design_scores_gemma":[0.000375977,0.002188668,0.9224025,0.00007773574,0.0003200551,0.000007633402,0.04480527,0.006831167,0.0004943846,0.02226961,0.0001495565,0.00007742903],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9815482,0.0005039524,0.009548012,0.006535483,0.00061139,0.0007811657,0.00008615787,0.000005084168,0.0003805355],"genre_scores_gemma":[0.9995892,0.00002174333,0.0001615003,0.00005891041,0.000041353,0.00009041674,0.000002411453,0.000003787849,0.00003066514],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4711755,"threshold_uncertainty_score":0.9783898,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1707793386271943,"score_gpt":0.4879068127812745,"score_spread":0.3171274741540802,"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."}}