{"id":"W7079686803","doi":"10.5281/zenodo.17031455","title":"Telomerina flavipes","year":2025,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Geochemistry and Geologic Mapping","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Nearctic ecozone; Czech; Moorland; Livestock","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":[0.0001521862,0.000687045,0.0002768225,0.001569442,0.001473926,0.000415014,0.0006270503,0.0004458742,0.01078158],"category_scores_gemma":[0.0004443416,0.000140645,0.0001595322,0.0007266201,0.0003598231,0.0006862984,0.0006333388,0.0003007264,0.003464442],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009353305,"about_ca_system_score_gemma":0.0002360469,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01351781,"about_ca_topic_score_gemma":0.02015756,"domain_scores_codex":[0.9998591,0.00001305563,0.000009068598,0.00006744319,0.00003110271,0.0000202366],"domain_scores_gemma":[0.9998462,0.00002042061,0.00006617761,0.00001517162,0.00003215703,0.0000198239],"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":[0.001320748,0.0002482016,0.1170195,0.001097781,0.0001338387,0.004430201,0.005149839,0.002022175,0.1073405,0.005763944,0.01989476,0.7355785],"study_design_scores_gemma":[0.0001145881,0.0004600327,0.5655249,0.0005727187,0.0001519417,0.007987989,0.001948584,0.0009908275,0.004551415,0.001469423,0.4161733,0.00005424189],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"other","genre_scores_codex":[0.7900601,0.01422836,0.004413683,0.0004745496,0.0003698391,0.0003295317,0.005931172,0.000655023,0.1835377],"genre_scores_gemma":[0.9666837,0.002060928,0.002621158,0.0002919911,0.0001480418,0.0001157463,0.002259687,0.00002338235,0.02579522],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.01351781,"threshold_uncertainty_score":0.03606802,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02123177691560323,"score_gpt":0.2337501076317181,"score_spread":0.2125183307161149,"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."}}