{"id":"W4246486212","doi":"10.1007/978-1-349-94186-5_1046","title":"Social Sciences and Humanities Research Council (SSHRC)","year":2018,"lang":"en","type":"book-chapter","venue":"Palgrave Macmillan UK eBooks","topic":"Research, Science, and Academia","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Medical Research Council; Arts and Humanities Research Council; Department of Science and Technology, Ministry of Science and Technology, India; Science and Engineering Research Board; Savoy Foundation; Society of Architectural Historians; Samuel H. Kress Foundation","keywords":"Research council; Humanities; Sociology; Library science; Art; Social science; Computer science; Philosophy; Linguistics","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":["metaresearch","metaepi_narrow","sts","scholarly_communication","insufficient_payload"],"consensus_categories":["sts","insufficient_payload"],"category_scores_codex":[0.03574397,0.0006174581,0.0009302204,0.001512889,0.003973769,0.002400081,0.003915033,0.0006293607,0.002760399],"category_scores_gemma":[0.003798944,0.0004474884,0.0002986753,0.0002942789,0.01690583,0.00001059734,0.001345289,0.001522972,0.001815024],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004942134,"about_ca_system_score_gemma":0.002656695,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001858548,"about_ca_topic_score_gemma":0.0008616505,"domain_scores_codex":[0.9761047,0.0004326775,0.001138429,0.002093531,0.01869811,0.001532566],"domain_scores_gemma":[0.9906381,0.002875585,0.0004672807,0.0009410901,0.004726806,0.0003511011],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00003389355,3.937733e-7,0.0001014329,0.00001909171,0.00002539203,0.00004059986,0.003542543,9.522961e-8,0.0001058463,0.9594364,0.0173254,0.0193689],"study_design_scores_gemma":[0.0002013206,0.0002477459,0.0003552937,0.00007809195,0.00001110363,0.00002477752,0.001202668,0.00003767785,0.00007067026,0.8354338,0.1618713,0.000465498],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.001698214,0.001560589,0.00001267963,0.00038166,0.0004053367,0.0005825248,0.0001068951,0.00006995242,0.9951822],"genre_scores_gemma":[0.796989,0.00021407,0.0001052097,0.0003218895,0.001654856,0.0000238146,0.000002824916,0.0000416849,0.2006466],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.7952908,"threshold_uncertainty_score":0.9997977,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.5383310357711445,"score_gpt":0.4535682482386975,"score_spread":0.08476278753244698,"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."}}