{"id":"W6949312032","doi":"10.5281/zenodo.13772841","title":"Gephyreaster swifti","year":2024,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Fern and Epiphyte Biology","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Tapering; Series (stratigraphy); Conical surface; Margin (machine learning); Bending","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":[0.00008930181,0.001009666,0.0003917392,0.001530618,0.001190371,0.000276832,0.0004671688,0.0005077215,0.01387798],"category_scores_gemma":[0.0002612132,0.000207783,0.0001715949,0.0007760216,0.0003851804,0.001425257,0.0009339942,0.0004389106,0.003683374],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008893997,"about_ca_system_score_gemma":0.0004311678,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008554161,"about_ca_topic_score_gemma":0.01417986,"domain_scores_codex":[0.9998815,0.000009563147,0.00000921868,0.0000435916,0.00003378565,0.00002240081],"domain_scores_gemma":[0.9999609,0.000005383686,0.00001236929,0.000003926438,0.00001067537,0.000006682677],"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":[0.0005199152,0.0001040655,0.03776591,0.001667969,0.00007840522,0.005462621,0.003446175,0.0007680368,0.04793715,0.01320367,0.04745302,0.8415931],"study_design_scores_gemma":[0.00007314338,0.0003401352,0.1851049,0.0007019923,0.00008380414,0.01070469,0.001655076,0.0007394839,0.004340568,0.003474992,0.7927353,0.00004588082],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4947677,0.03704798,0.010093,0.001486737,0.001263477,0.0006737238,0.004624637,0.000668578,0.4493742],"genre_scores_gemma":[0.8977479,0.01079972,0.007012461,0.0008872265,0.0003592032,0.0002941625,0.0026288,0.00003484478,0.08023584],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01387798,"threshold_uncertainty_score":0.04642648,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03831837674899846,"score_gpt":0.2256662486008929,"score_spread":0.1873478718518944,"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."}}