{"id":"W4401124450","doi":"10.1111/jne.13436","title":"Announcement: Gregory F. Ball wins the 2024 Donald S. Farner Medal for Excellence in Research in the Field of Avian Endocrinology","year":2024,"lang":"en","type":"editorial","venue":"Journal of Neuroendocrinology","topic":"Reproductive Physiology in Livestock","field":"Agricultural and Biological Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Division of Graduate Education; Johns Hopkins University; National Institutes of Health; National Science Foundation","keywords":"Excellence; Medal; Internal medicine; Endocrinology; Medicine; Management; Art; Art history; Political science; Law; Economics","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":"codex-gemma-dda1882f352a","candidate_categories":["research_integrity"],"consensus_categories":[],"category_scores_codex":[0.00109046,0.000328134,0.0007938307,0.000264868,0.000139902,0.00004526378,0.002522265,0.0003949231,0.00007206993],"category_scores_gemma":[0.002742645,0.0001086113,0.0003321872,0.0007706533,0.0008077177,0.0001189687,0.0004799284,0.005725827,0.00001269235],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009091563,"about_ca_system_score_gemma":0.0001703195,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003951173,"about_ca_topic_score_gemma":0.0006652417,"domain_scores_codex":[0.9945648,0.00183528,0.00114233,0.0006828346,0.0008381789,0.0009366093],"domain_scores_gemma":[0.9832771,0.0152219,0.0005669367,0.0003023501,0.000582305,0.00004941115],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0006514273,0.0002659325,0.0004182431,0.0000966903,0.00008038386,0.000677746,0.000284517,0.00002313885,0.01405792,0.0008642164,0.9781936,0.004386142],"study_design_scores_gemma":[0.0003870935,0.006261027,0.007495925,0.0001383702,0.00004567645,0.0003516113,0.0008188143,0.000004502091,0.0002260306,0.01318539,0.970923,0.0001625248],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"editorial","genre_gemma":"editorial","genre_scores_codex":[0.3136088,0.007671525,0.000001344583,0.1590944,0.516876,0.001570652,0.0001927611,0.00001365582,0.0009708559],"genre_scores_gemma":[0.4282219,0.01134445,0.00004767799,0.001511124,0.5563167,0.0003727741,0.00005889932,0.00001747527,0.002109006],"genre_candidate":"editorial","genre_consensus":"editorial","teacher_disagreement_score":0.1575833,"threshold_uncertainty_score":0.996568,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07771137170029792,"score_gpt":0.3735421828141334,"score_spread":0.2958308111138355,"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."}}