{"id":"W6931506096","doi":"10.5281/zenodo.7019676","title":"Empria improba","year":2022,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Efficiency Analysis Using DEA","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Homonym (biology); Type (biology); Taxon; Nomenclature; Taxonomy (biology)","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":[],"consensus_categories":[],"category_scores_codex":[0.000206493,0.0009010684,0.0003452705,0.001452499,0.002534424,0.0008822583,0.000717659,0.0005385092,0.05164871],"category_scores_gemma":[0.000504198,0.0002120966,0.0001670771,0.0009100001,0.0009039914,0.001216549,0.001555102,0.0010469,0.01171053],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009412146,"about_ca_system_score_gemma":0.0005510245,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005727525,"about_ca_topic_score_gemma":0.01297905,"domain_scores_codex":[0.9997881,0.00002770003,0.00001025541,0.00006705374,0.00006381499,0.00004314629],"domain_scores_gemma":[0.999845,0.00002694379,0.00003419726,0.00002469348,0.00004713834,0.00002199667],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002984234,0.0001222397,0.009116415,0.0005824942,0.00001405599,0.002077197,0.001757478,0.00031526,0.006821523,0.01746833,0.0539602,0.9074664],"study_design_scores_gemma":[0.00002477279,0.00007191119,0.04738104,0.0003273065,0.00001679494,0.002647918,0.001093366,0.0002810764,0.001517768,0.001952279,0.9446728,0.00001288146],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.07542574,0.006725115,0.003888653,0.0007929825,0.0005732506,0.0002341114,0.001374666,0.0008376867,0.9101477],"genre_scores_gemma":[0.7352822,0.004707827,0.007825847,0.001073411,0.000396508,0.0003194209,0.002600538,0.0002086465,0.2475857],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.05164871,"threshold_uncertainty_score":0.1727821,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.098543007280478,"score_gpt":0.3317928989397163,"score_spread":0.2332498916592383,"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."}}