{"id":"W6931318121","doi":"10.5281/zenodo.15801418","title":"Parapterogramma bicolor Kuwahara, Marshall & Luk, 2025, sp. nov.","year":2025,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Data Analysis with R","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"","keywords":"Holotype; Mount; Etymology; Data collection","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":[0.0001622867,0.001464465,0.0006311036,0.003864318,0.003244242,0.0009007517,0.001116508,0.0012571,0.01269891],"category_scores_gemma":[0.0006105484,0.0004880136,0.0003045703,0.002380042,0.0008211656,0.002669048,0.0009922544,0.001091898,0.00688075],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001246026,"about_ca_system_score_gemma":0.0007406295,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02748205,"about_ca_topic_score_gemma":0.0609926,"domain_scores_codex":[0.9997432,0.00002133176,0.0000365,0.00009915741,0.00005303871,0.00004682949],"domain_scores_gemma":[0.9997022,0.00003697744,0.0001115748,0.00004435406,0.00007222591,0.0000327432],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001299112,0.0002567164,0.05187186,0.002938902,0.0002875106,0.005329381,0.003424207,0.0009936987,0.03721167,0.002933308,0.07731522,0.8161384],"study_design_scores_gemma":[0.0002573598,0.0003070857,0.5014888,0.001866601,0.000484313,0.01890571,0.004925807,0.0008661977,0.003398512,0.001220113,0.4661401,0.0001394489],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"other","genre_scores_codex":[0.4781675,0.05982505,0.01352407,0.002803393,0.003474018,0.00355049,0.04162612,0.002709618,0.3943197],"genre_scores_gemma":[0.8905639,0.01931418,0.01779113,0.002429222,0.000434289,0.001681373,0.01602559,0.0003039131,0.05145641],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.02748205,"threshold_uncertainty_score":0.05464423,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03144767293838577,"score_gpt":0.2623530331461454,"score_spread":0.2309053602077597,"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."}}