{"id":"W4390228573","doi":"10.1080/04353684.2023.2296572","title":"Knowledge transfers from business conferences to firms’ permanent locations","year":2023,"lang":"en","type":"article","venue":"Geografiska Annaler Series B Human Geography","topic":"Conferences and Exhibitions Management","field":"Social Sciences","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Social Sciences and Humanities Research Council of Canada; Friedrich-Schiller-Universität Jena","keywords":"Closing (real estate); Knowledge transfer; Face (sociological concept); Business; Process (computing); Knowledge management; Field (mathematics); Business development; Marketing; Computer science; Data science; Sociology; Finance","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003949759,0.0002786052,0.0003224402,0.002824041,0.006326209,0.006206687,0.001666603,0.001770709,0.009142823],"category_scores_gemma":[0.0230532,0.0002670552,0.0002873747,0.00204162,0.004878639,0.004728293,0.008344064,0.001736881,0.0007955502],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00525944,"about_ca_system_score_gemma":0.004232558,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01602437,"about_ca_topic_score_gemma":0.02174835,"domain_scores_codex":[0.9947174,0.002620403,0.0001360004,0.0006068734,0.0005632404,0.001356018],"domain_scores_gemma":[0.9807504,0.01046997,0.002534879,0.002258368,0.001459669,0.002526839],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"observational","study_design_scores_codex":[0.0003691101,0.0004061628,0.0869257,0.0005187605,0.00006881487,0.004593908,0.5664408,0.002371443,0.004360096,0.04209775,0.008896698,0.2829508],"study_design_scores_gemma":[0.00004472216,0.0002696996,0.09277251,0.000399527,0.00003723674,0.0005980546,0.8162906,0.001539209,0.001787472,0.01324347,0.07293855,0.00007907436],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9264879,0.0005062463,0.004334355,0.003269035,0.00009295675,0.0001177177,0.0001041974,0.00007991729,0.06500761],"genre_scores_gemma":[0.9969345,0.0001177592,0.0004409702,0.0000816946,0.00001669751,0.00001933906,0.00003120484,0.000007321446,0.002350526],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01602437,"threshold_uncertainty_score":0.03816009,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04358324116909163,"score_gpt":0.3114673925837909,"score_spread":0.2678841514146993,"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."}}