{"id":"W6892852129","doi":"10.5281/zenodo.12765725","title":"Urophora affinis","year":2016,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Collembola Taxonomy and Ecology Studies","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Middle East; Western europe; Biogeography; Distribution (mathematics)","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":[0.000193018,0.000743638,0.0003703721,0.002628824,0.003145182,0.0005896565,0.0004455347,0.0007228064,0.01091127],"category_scores_gemma":[0.0005691091,0.0002544044,0.000232613,0.001228355,0.0006555218,0.001165645,0.0009127684,0.00052219,0.002271238],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008701245,"about_ca_system_score_gemma":0.0004738728,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01084486,"about_ca_topic_score_gemma":0.0219362,"domain_scores_codex":[0.9997643,0.00002717836,0.000017891,0.00007764177,0.00006466434,0.00004831469],"domain_scores_gemma":[0.9998234,0.00003845021,0.00006519003,0.00001433205,0.00004043081,0.00001827307],"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":[0.000242779,0.0001695103,0.06392846,0.0007766774,0.00005311467,0.001914362,0.002516376,0.0005837189,0.02159393,0.004115426,0.0131877,0.890918],"study_design_scores_gemma":[0.00004900518,0.0002505938,0.6062701,0.001002266,0.00009262312,0.007282528,0.00327896,0.0005707156,0.003872261,0.003117593,0.374166,0.00004739147],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6003357,0.04047134,0.00449942,0.0008602425,0.0005863615,0.0005213278,0.004579682,0.0006350497,0.3475109],"genre_scores_gemma":[0.9734142,0.004235923,0.003178763,0.0004211415,0.0001474209,0.0000899286,0.001185919,0.00002171814,0.01730505],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01091127,"threshold_uncertainty_score":0.03650188,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04020346570973832,"score_gpt":0.205675631034911,"score_spread":0.1654721653251727,"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."}}