{"id":"W1987487032","doi":"10.1109/mc.2014.61","title":"Identifying Knowledge Brokers and Their Role in Enterprise Research through Social Media","year":2014,"lang":"en","type":"article","venue":"Computer","topic":"Mobile Crowdsensing and Crowdsourcing","field":"Computer Science","cited_by":20,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Institute of Standards and Technology; Canada Excellence Research Chairs, Government of Canada; National Science Foundation","keywords":"Seekers; Computer science; Identifier; Function (biology); Knowledge management; Social media; World Wide Web; Data science","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001178603,0.000143347,0.00020934,0.0001831122,0.0003535692,0.0005581956,0.0005795337,0.00008654688,0.000003137542],"category_scores_gemma":[0.00004606481,0.0001274741,0.00005165926,0.0004017964,0.0001757504,0.0003280647,0.0008198261,0.0003498608,0.00005090866],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004887691,"about_ca_system_score_gemma":0.0000402412,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003462813,"about_ca_topic_score_gemma":0.00007750677,"domain_scores_codex":[0.9982547,0.0003896801,0.0002144126,0.0004900909,0.0001946698,0.0004564569],"domain_scores_gemma":[0.998827,0.0006066725,0.0000390504,0.0003648541,0.00008730626,0.00007506946],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000008707608,0.0001105188,0.001610897,0.00005651875,0.0000158319,0.00001396986,0.1584893,0.00004505645,0.001574264,0.02287735,0.005160514,0.8100371],"study_design_scores_gemma":[0.002093203,0.0001509492,0.03625156,0.0005346574,0.000005887007,0.0000737657,0.001847139,0.7998537,0.004396417,0.0774058,0.0764676,0.0009193727],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4016984,0.0005773368,0.5934229,0.0003804788,0.0007362332,0.0001098172,4.902043e-7,0.0001359864,0.0029384],"genre_scores_gemma":[0.9867256,0.000011484,0.01251187,0.0001405047,0.0005515061,0.000006413566,0.000001043263,0.00001327087,0.00003835535],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8091177,"threshold_uncertainty_score":0.5382693,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05162614771730138,"score_gpt":0.3153048983930349,"score_spread":0.2636787506757335,"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."}}