{"id":"W2808574250","doi":"10.13140/rg.2.1.3769.2406/1","title":"EDDA Study Designs Taxonomy (version 2.0)","year":2016,"lang":"en","type":"article","venue":"D-Scholarship@Pitt (University of Pittsburgh)","topic":"Biomedical Text Mining and Ontologies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Terminology; Taxonomy (biology); Plural; Library science; Subject (documents); Computer science; Information retrieval; Linguistics; Philosophy","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.1045491,0.001999109,0.005164268,0.02355075,0.002132934,0.007316092,0.005000576,0.002943282,0.110077],"category_scores_gemma":[0.2315759,0.004806741,0.008655761,0.02534983,0.001714965,0.005523908,0.007430243,0.006823457,0.02304914],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.006650819,"about_ca_system_score_gemma":0.0310624,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007502079,"about_ca_topic_score_gemma":0.01194265,"domain_scores_codex":[0.9112713,0.03514062,0.03878637,0.003171757,0.01026065,0.001369225],"domain_scores_gemma":[0.7568716,0.16833,0.01906102,0.0150186,0.03852281,0.002196017],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.001285405,0.0002006904,0.004051215,0.116438,0.001127019,0.0001700518,0.005230588,0.002680314,0.0007440413,0.05190643,0.5039257,0.3122406],"study_design_scores_gemma":[0.000816713,0.0002049467,0.003784952,0.02087938,0.0005634441,0.0001790494,0.0008730713,0.0009446096,0.0002902628,0.02857687,0.9427536,0.0001331727],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"methods","genre_scores_codex":[0.003253295,0.01483423,0.2563763,0.005176091,0.001494855,0.1421109,0.5323448,0.009361018,0.03504856],"genre_scores_gemma":[0.004679877,0.006473816,0.5426077,0.001723085,0.0002118916,0.3453965,0.09006514,0.002015569,0.00682645],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8954509,"threshold_uncertainty_score":0.552915,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05116250546775349,"score_gpt":0.2489181448389418,"score_spread":0.1977556393711883,"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."}}