{"id":"W7079852462","doi":"10.5281/zenodo.17031551","title":"Hydrellia griseola","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":"Hay; China; Czech; Chine; Exportation","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":[0.0001549425,0.0007575852,0.0003114518,0.001286975,0.001692933,0.000335786,0.0005452753,0.000487669,0.01565825],"category_scores_gemma":[0.0003809711,0.0001918071,0.0001744893,0.0005009928,0.0005422728,0.0007055223,0.0009660987,0.000493581,0.003604675],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009808723,"about_ca_system_score_gemma":0.0003530098,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01742528,"about_ca_topic_score_gemma":0.03302863,"domain_scores_codex":[0.9998585,0.00001622143,0.000008129669,0.00005717835,0.00002896426,0.00003097378],"domain_scores_gemma":[0.999887,0.00002229386,0.00003180276,0.00001129332,0.00002187863,0.00002561772],"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":[0.001589583,0.0002952245,0.0853088,0.002522669,0.0001260947,0.01018707,0.005319724,0.002324301,0.1020462,0.00998041,0.04203996,0.7382601],"study_design_scores_gemma":[0.000166096,0.00040974,0.474688,0.0006637544,0.00008718685,0.008933457,0.001854779,0.0007688151,0.005275689,0.00247727,0.5046186,0.00005666306],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6853356,0.02037949,0.004208762,0.001419582,0.0006935621,0.0006303363,0.01031026,0.0009356412,0.2760868],"genre_scores_gemma":[0.9581704,0.002337112,0.003227661,0.0009273889,0.0001816779,0.0001004271,0.002827954,0.00002973741,0.03219753],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01742528,"threshold_uncertainty_score":0.05238211,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02132860386753476,"score_gpt":0.22883282255249,"score_spread":0.2075042186849552,"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."}}