{"id":"W3182380638","doi":"10.1287/mnsc.2021.4032","title":"Stars and Brokers: Knowledge Spillovers Among Medical Scientists","year":2021,"lang":"en","type":"article","venue":"Management Science","topic":"scientometrics and bibliometrics research","field":"Decision Sciences","cited_by":62,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"Position (finance); Productivity; Degree (music); Identification (biology); Measure (data warehouse); Entrepreneurship; Star (game theory); Computer science; Industrial organization; Economics; Mathematics; Economic growth; Physics; Finance","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":[0.006139241,0.0002751319,0.0006850574,0.003077963,0.0006653985,0.002110468,0.0005173179,0.0008968774,0.004291655],"category_scores_gemma":[0.04597048,0.0002430507,0.0006784048,0.003314744,0.001417187,0.002872778,0.002166968,0.0006897587,0.0004086572],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008744076,"about_ca_system_score_gemma":0.0006053483,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002489733,"about_ca_topic_score_gemma":0.001940017,"domain_scores_codex":[0.996313,0.001942846,0.0002200065,0.0006595433,0.0005746084,0.0002899595],"domain_scores_gemma":[0.9307092,0.05102094,0.01327123,0.001915156,0.001029999,0.002053417],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0009878315,0.0001691945,0.8926252,0.0002918607,0.0007969959,0.0003976008,0.003123533,0.01560378,0.001778551,0.02517685,0.001212545,0.05783615],"study_design_scores_gemma":[0.0002327675,0.0009008024,0.857821,0.0001843411,0.00110758,0.001095966,0.003643306,0.06180727,0.00304759,0.06392746,0.006133652,0.0000981175],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9777013,0.001841202,0.01209848,0.001378968,0.00002913391,0.00004094505,0.0003185109,0.00003998294,0.006551426],"genre_scores_gemma":[0.998557,0.0001756693,0.0007032813,0.00002955429,0.0000349052,0.000007221197,0.0000646363,0.000002233263,0.0004255571],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.996922,"threshold_uncertainty_score":0.03246778,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3401180911245082,"score_gpt":0.5539872394611265,"score_spread":0.2138691483366183,"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."}}