{"id":"W4233177583","doi":"10.21307/connections-2019-010","title":"Academic Collaboration via Resource Contributions: An Egocentric Dataset","year":2019,"lang":"en","type":"article","venue":"Connections","topic":"Mental Health and Patient Involvement","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Resource (disambiguation); Incentive; Knowledge management; Coding (social sciences); Data science; Qualitative property; Process (computing); Order (exchange); Computer science; Sociology; Business; Social science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["bibliometrics"],"consensus_categories":[],"category_scores_codex":[0.001881202,0.0002381933,0.0002336461,0.003780742,0.0009577491,0.0012418,0.0006349764,0.0006152167,0.003228319],"category_scores_gemma":[0.01031731,0.0001535215,0.0002754343,0.007431587,0.0004805058,0.001198982,0.002354298,0.0004913674,0.001284911],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009875679,"about_ca_system_score_gemma":0.001018676,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01445414,"about_ca_topic_score_gemma":0.02359179,"domain_scores_codex":[0.9979779,0.0009453229,0.0001793549,0.000325163,0.0003672313,0.0002049319],"domain_scores_gemma":[0.9925798,0.002996282,0.001467457,0.001448062,0.000910474,0.0005979639],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0006808444,0.0005326145,0.806846,0.0007050275,0.0002538743,0.0004914391,0.009572435,0.006538578,0.002402943,0.01996627,0.09068944,0.06132042],"study_design_scores_gemma":[0.00009886264,0.0001390985,0.7337263,0.000202666,0.00007542974,0.0005356194,0.01391025,0.0172836,0.001940437,0.01084897,0.2211397,0.00009906686],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"dataset","genre_scores_codex":[0.7348059,0.0003119564,0.005821921,0.0007844126,0.00002540544,0.0002391639,0.2469956,0.0002318377,0.01078383],"genre_scores_gemma":[0.6993279,0.0002515502,0.01195614,0.0001414964,0.00002940025,0.0006848084,0.2851603,0.00005433203,0.002393944],"genre_candidate":"dataset","genre_consensus":null,"teacher_disagreement_score":0.9962193,"threshold_uncertainty_score":0.02873999,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1267720695986431,"score_gpt":0.4580538839291026,"score_spread":0.3312818143304594,"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."}}