{"id":"W6893108097","doi":"10.5281/zenodo.14597225","title":"Neopolynemoidea chilensis Huber 2022","year":2024,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Subterranean biodiversity and taxonomy","field":"Earth and Planetary Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Natural Resources Canada","funders":"","keywords":"Holotype; Selection (genetic algorithm); Key (lock)","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":[0.0001445346,0.0004775463,0.0001741831,0.001603926,0.0008302883,0.0005092048,0.0005189872,0.0003613342,0.02465279],"category_scores_gemma":[0.000295588,0.0001898935,0.0001350641,0.001041327,0.0002971746,0.0008493849,0.0008658742,0.0006024041,0.006075984],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001100731,"about_ca_system_score_gemma":0.001321366,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02620823,"about_ca_topic_score_gemma":0.04420818,"domain_scores_codex":[0.9999073,0.000006555846,0.000006453395,0.00002180005,0.00003355286,0.00002440226],"domain_scores_gemma":[0.9998229,0.00001118595,0.00003872349,0.00001886701,0.00007864998,0.00002961502],"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":[0.0002575355,0.00009187432,0.03941772,0.001216762,0.00005704726,0.001077351,0.00286239,0.0005853662,0.03495443,0.008967505,0.1262967,0.7842153],"study_design_scores_gemma":[0.00005282742,0.0000379438,0.1902477,0.0004911673,0.00002841331,0.001107711,0.001115751,0.0001787452,0.003184991,0.001253497,0.8022714,0.00002983403],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.2417111,0.01706945,0.005026831,0.001986602,0.0006295295,0.0009036319,0.02347586,0.001380453,0.7078164],"genre_scores_gemma":[0.6718299,0.01208623,0.00816415,0.001373945,0.0002689334,0.0007876265,0.0182862,0.0002498835,0.2869531],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02620823,"threshold_uncertainty_score":0.08247179,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04075843876063608,"score_gpt":0.1996350100411423,"score_spread":0.1588765712805063,"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."}}