{"id":"W6949054702","doi":"10.5281/zenodo.12517918","title":"Argyresthia conjugella Zeller 1839","year":2024,"lang":"en","type":"article","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":"Distribution (mathematics); Subject (documents); Ceylon; Government (linguistics)","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":[0.0001304316,0.0004484233,0.0002834128,0.0009268479,0.001136445,0.0004385214,0.0004396832,0.0004899311,0.01252123],"category_scores_gemma":[0.0004282827,0.0001310485,0.0001245442,0.0008741674,0.0005061202,0.0009601337,0.0008075494,0.0004574151,0.005281863],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004554945,"about_ca_system_score_gemma":0.0002480444,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003397163,"about_ca_topic_score_gemma":0.004687272,"domain_scores_codex":[0.999831,0.00001996929,0.00002322417,0.00005589927,0.00004254783,0.00002737909],"domain_scores_gemma":[0.9998527,0.00002965013,0.00005972208,0.00001680548,0.00002795076,0.00001311824],"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":[0.0007649331,0.0001215441,0.0937132,0.001712671,0.0001159209,0.005324398,0.006042854,0.001266758,0.06549134,0.007665327,0.02801328,0.7897678],"study_design_scores_gemma":[0.00006892859,0.0002471957,0.3312167,0.000538837,0.0001117987,0.008589968,0.003842527,0.0003913419,0.009248817,0.002066224,0.6436204,0.00005729174],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6068555,0.02051923,0.00702231,0.001279962,0.001769083,0.0004139908,0.01061823,0.0006910518,0.3508307],"genre_scores_gemma":[0.9693922,0.002821373,0.003315801,0.000327856,0.0002002944,0.00007602114,0.002971688,0.00003261423,0.0208621],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01252123,"threshold_uncertainty_score":0.0418877,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0371660991556854,"score_gpt":0.2456677365358869,"score_spread":0.2085016373802015,"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."}}