{"id":"W4318328604","doi":"10.24394/natsom.2009.13.9","title":"Nagygomba-felmérés Gyűrűfű környékén","year":2009,"lang":"en","type":"article","venue":"Natura Somogyiensis","topic":"Forest Ecology and Biodiversity Studies","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Office of the Chief Medical Examiner","funders":"","keywords":"Taxon; Biodiversity; Biology; Global biodiversity; Ecology; Forestry; Botany; Geography","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001157103,0.0004140569,0.0004021192,0.0005638341,0.0007853041,0.0005100345,0.0002654375,0.0002641446,0.01934779],"category_scores_gemma":[0.0001419245,0.0001595598,0.0002178518,0.0004403449,0.000341752,0.0002215754,0.0009050519,0.000255759,0.00297488],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004230564,"about_ca_system_score_gemma":0.0004138975,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003839672,"about_ca_topic_score_gemma":0.009206985,"domain_scores_codex":[0.999898,0.00001156181,0.000004806572,0.0000346607,0.00001116637,0.00003978221],"domain_scores_gemma":[0.9999678,0.000005808089,0.000008237751,0.000003787344,0.000003039776,0.00001121301],"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":[0.001693329,0.0003563756,0.1544572,0.002469701,0.0002600396,0.0188528,0.004010927,0.002782867,0.04022921,0.009165841,0.02240958,0.7433121],"study_design_scores_gemma":[0.00008581671,0.0002929661,0.7861539,0.00031619,0.00006960978,0.009043614,0.002145928,0.0006414803,0.002767347,0.001734323,0.1967091,0.0000397078],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9340465,0.01019242,0.001829126,0.0003561555,0.0002690758,0.0001338411,0.005085956,0.0001745031,0.04791235],"genre_scores_gemma":[0.9447606,0.004273426,0.003931197,0.0001407721,0.00007824642,0.0001397988,0.00431058,0.00006023951,0.04230517],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01934779,"threshold_uncertainty_score":0.0647248,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0111671455878277,"score_gpt":0.195659435022361,"score_spread":0.1844922894345333,"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."}}