{"id":"W6949320812","doi":"10.5281/zenodo.14976034","title":"Calycomyza solidaginis","year":2025,"lang":"en","type":"other","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Species Distribution and Climate Change","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Herbaceous plant; Vegetation (pathology); Variety (cybernetics); Biodiversity","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":[0.0001018025,0.0005227427,0.000309177,0.0009459443,0.001601907,0.0003685064,0.0003415566,0.0004341543,0.01138545],"category_scores_gemma":[0.0004339712,0.0001215654,0.0001242172,0.0007505869,0.0007873988,0.0006455763,0.001195455,0.0005574421,0.002059221],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001075446,"about_ca_system_score_gemma":0.000575814,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01693168,"about_ca_topic_score_gemma":0.03436672,"domain_scores_codex":[0.9998492,0.00001320897,0.000009078304,0.00005542593,0.00005201226,0.00002110894],"domain_scores_gemma":[0.9998555,0.00002303054,0.00004795149,0.00001233625,0.00003303102,0.00002811515],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.001180769,0.0001444778,0.02689945,0.002254607,0.00009838998,0.009093783,0.002537898,0.004639727,0.2148083,0.01974522,0.04578097,0.6728165],"study_design_scores_gemma":[0.0001908783,0.000339432,0.2361888,0.0005476535,0.00007669663,0.007254379,0.001681142,0.001677582,0.00865021,0.002681763,0.7406719,0.00003961446],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6026516,0.0139553,0.007212422,0.001897724,0.0007707409,0.0003992091,0.006361627,0.0004306303,0.3663208],"genre_scores_gemma":[0.9583961,0.001937658,0.002751724,0.0005420388,0.0001188537,0.00008376867,0.002063874,0.00002581195,0.03408021],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01693168,"threshold_uncertainty_score":0.03808808,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02992162555776555,"score_gpt":0.2463411435673794,"score_spread":0.2164195180096138,"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."}}