{"id":"W2966011811","doi":"","title":"Are Altmetrics Effective in Transdisciplinary Research Fields? - Altmetric Coverage of Outputs in Educational Research.","year":2017,"lang":"en","type":"article","venue":"Ingénierie des systèmes d information","topic":"Interdisciplinary Research and Collaboration","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Altmetrics; Computer science; Data 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":["metaresearch","bibliometrics"],"consensus_categories":[],"category_scores_codex":[0.06865235,0.0008705349,0.001321136,0.0290866,0.001689725,0.009621981,0.001755721,0.001483008,0.01017515],"category_scores_gemma":[0.324536,0.0004401202,0.001084002,0.04990814,0.003655973,0.01621705,0.008200283,0.001279474,0.003075896],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002997041,"about_ca_system_score_gemma":0.003336498,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002748422,"about_ca_topic_score_gemma":0.003311655,"domain_scores_codex":[0.9261441,0.04007598,0.006596979,0.003929848,0.02161559,0.00163733],"domain_scores_gemma":[0.6518589,0.1885055,0.06402129,0.03057383,0.06043806,0.004602355],"domain_codex":null,"domain_gemma":"evaluation","domain_candidate":"evaluation","domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0006211752,0.0001314824,0.3671098,0.002255395,0.0004777272,0.0001096195,0.006204088,0.002136727,0.001318077,0.05318189,0.02372944,0.5427247],"study_design_scores_gemma":[0.0001077389,0.000656734,0.6621274,0.00335251,0.0006884282,0.001003452,0.02235804,0.0151918,0.007372254,0.1122614,0.1746912,0.0001890253],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.499624,0.04086001,0.1378173,0.03813014,0.001453285,0.0004107073,0.02074702,0.003254361,0.2577032],"genre_scores_gemma":[0.9558151,0.003967009,0.03078189,0.0008280337,0.0007376297,0.0003148069,0.003510879,0.0003078668,0.003736677],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9709134,"threshold_uncertainty_score":0.3630726,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1899188411059195,"score_gpt":0.4676518739699754,"score_spread":0.2777330328640559,"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."}}