{"id":"W2606235571","doi":"10.1186/s13742-016-0147-0-f","title":"Automatic extraction of academic collaborations in neuroimaging","year":2016,"lang":"en","type":"article","venue":"GigaScience","topic":"scientometrics and bibliometrics research","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"","keywords":"Neuroimaging; Computer science; Extraction (chemistry); Data science; Artificial intelligence; Neuroscience; Chemistry; Psychology; Chromatography","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":["metaresearch","bibliometrics"],"consensus_categories":["bibliometrics"],"category_scores_codex":[0.01437812,0.00006711669,0.0001553376,0.02715133,0.0001026697,0.0002867684,0.001684961,0.00004895034,0.0003158183],"category_scores_gemma":[0.04826321,0.00003836458,0.00003894445,0.1709294,0.0003316453,0.001556265,0.0002478787,0.000134435,0.0001849842],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008683061,"about_ca_system_score_gemma":0.0003345782,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002777457,"about_ca_topic_score_gemma":0.00001700896,"domain_scores_codex":[0.9935879,0.0001564539,0.0006396765,0.0004636613,0.004781805,0.0003705207],"domain_scores_gemma":[0.9942276,0.003791206,0.0002487338,0.0004640404,0.001108143,0.0001602722],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.000002860164,0.00004542282,0.2983263,0.000002156489,5.856857e-7,0.000005105941,0.0001356842,0.00003810305,0.2883255,0.001888091,0.001408466,0.4098217],"study_design_scores_gemma":[0.0002965362,0.00005918631,0.9487764,0.00003090357,0.000001009468,0.000009228966,0.0002533432,0.02132423,0.01550583,0.01107083,0.002570466,0.000102067],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9837534,0.0001210735,0.01104067,0.002618497,0.0003377526,0.0001320006,0.000009262607,0.00001606324,0.001971236],"genre_scores_gemma":[0.9981219,0.00009239544,0.001101152,0.00005281965,0.00001487411,0.000006635496,9.087154e-8,0.000002940401,0.00060723],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6504501,"threshold_uncertainty_score":0.9838751,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.5944381460399508,"score_gpt":0.6029800787514076,"score_spread":0.008541932711456757,"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."}}