{"id":"W7133974242","doi":"10.3167/trans.2025.150301","title":"Editorial","year":2025,"lang":"","type":"article","venue":"Transfers","topic":"Human-Animal Interaction Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Wife; Government (linguistics); Work (physics); Plank; Pipeline (software)","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001323403,0.0002500808,0.0002370985,0.00007449304,0.0001925377,0.00005400987,0.000216391,0.0003217942,0.0002326982],"category_scores_gemma":[0.00006015578,0.0002702566,0.0002461025,0.0001370677,0.0001982194,0.000004231772,0.00005432683,0.0002446884,0.0001137641],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004229803,"about_ca_system_score_gemma":0.000186831,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003181882,"about_ca_topic_score_gemma":0.00009367452,"domain_scores_codex":[0.9986445,0.00006759023,0.0003225202,0.0004678743,0.0001611532,0.0003363412],"domain_scores_gemma":[0.9994069,0.00002444592,0.00002434456,0.000295834,0.0001790005,0.00006950956],"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":[0.0006966473,0.0001232754,0.0002239603,0.00007586608,0.0007020247,0.000001596274,0.0002127487,0.00001324458,0.247783,0.0007978206,0.7446267,0.004743143],"study_design_scores_gemma":[0.0009253789,0.0003637572,0.0001628919,0.00004141879,0.000132001,7.876749e-7,0.0003517344,0.000005801151,0.08756956,0.00005589574,0.9101723,0.0002184839],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"editorial","genre_gemma":"empirical","genre_scores_codex":[0.1647088,0.005037542,0.005451687,0.004221916,0.511627,0.0007616533,0.0001694326,0.00006471913,0.3079572],"genre_scores_gemma":[0.9462243,0.001278198,0.00002968691,0.0004729664,0.04216317,0.00002415272,0.00002159926,0.00001812763,0.009767747],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7815156,"threshold_uncertainty_score":0.999975,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01024478923829901,"score_gpt":0.337653121528618,"score_spread":0.327408332290319,"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."}}