{"id":"W6930408567","doi":"10.5281/zenodo.14207480","title":"Rediscovery of the greater chestnut weevil highlights the power of digital platforms in biodiversity research and conservation","year":2025,"lang":"en","type":"dataset","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Advanced NMR Techniques and Applications","field":"Chemistry","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Canadian Museum of Nature","funders":"","keywords":"Biodiversity; Weevil; Biodiversity conservation; Power (physics)","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":[0.001006205,0.001377527,0.0008340958,0.003542098,0.0007429767,0.001864544,0.001504053,0.001658037,0.02113198],"category_scores_gemma":[0.003561942,0.0003392353,0.001089981,0.004997414,0.0005032444,0.001176714,0.002019879,0.001412665,0.02415961],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001041042,"about_ca_system_score_gemma":0.001374008,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04357658,"about_ca_topic_score_gemma":0.0970228,"domain_scores_codex":[0.9990419,0.0001561192,0.00007030584,0.0003268227,0.0002537435,0.0001510657],"domain_scores_gemma":[0.9982933,0.0005460769,0.0001975495,0.0004434263,0.0003439278,0.0001757069],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.0002719042,0.00004606246,0.005090788,0.00171974,0.0001112726,0.0001084679,0.000122776,0.001397155,0.001282816,0.001608999,0.9747604,0.01347976],"study_design_scores_gemma":[0.00009064893,0.00002010974,0.01802371,0.0003340731,0.00005115676,0.0001023025,0.0001700514,0.0007030423,0.0006716209,0.001698524,0.9781011,0.00003368134],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.001533277,0.000464758,0.000160248,0.000202257,0.00007801012,0.0000067865,0.995384,0.0004039377,0.001766685],"genre_scores_gemma":[0.002226274,0.0001995029,0.0003663255,0.00006972608,0.000009717926,0.00001717343,0.9961793,0.00007104762,0.0008608773],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.04357658,"threshold_uncertainty_score":0.08664584,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03741648426394802,"score_gpt":0.2650854830036217,"score_spread":0.2276689987396737,"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."}}