{"id":"W6893407171","doi":"10.5281/zenodo.16815812","title":"DEPRECATED: Matcher (Version 1) for Automated Task Alignment in the Genomic API for Model Evaluation (GAME)","year":2025,"lang":"en","type":"other","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Biomedical Text Mining and Ontologies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Task (project management); Container (type theory); Python (programming language); Transcription (linguistics); Matching (statistics); Ontology alignment; Key (lock); Graph","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009550577,0.0001672283,0.0001541288,0.0001469893,0.0003081747,0.000131447,0.0007334458,0.0002962794,0.0007786548],"category_scores_gemma":[0.0005007094,0.0001419736,0.00007554208,0.000134591,0.00009630554,0.0000030049,0.0003597894,0.0001109485,0.0001882669],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008919426,"about_ca_system_score_gemma":0.00002302726,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001684254,"about_ca_topic_score_gemma":0.000002482033,"domain_scores_codex":[0.9986184,0.0002268375,0.0002003537,0.0004528304,0.0002303345,0.000271226],"domain_scores_gemma":[0.9992077,0.00001913014,0.0001233746,0.0004027966,0.0002018722,0.00004506683],"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":[0.00009301233,0.00007531637,4.083521e-7,0.0001143113,0.00006552887,4.700546e-7,0.0001717233,0.0002942695,0.008051567,0.00009055652,0.9431049,0.04793797],"study_design_scores_gemma":[0.0009798862,0.000199407,0.00001997893,0.00005868738,0.00004656875,0.000004225167,0.0001608165,0.02150123,0.0003968781,0.0001378124,0.9763368,0.0001577122],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.007804419,0.005541088,0.2669595,0.005208921,0.0009529184,0.01527485,0.008278722,0.003122093,0.6868575],"genre_scores_gemma":[0.2530097,0.002767937,0.02207872,0.003225509,0.001769652,0.00002982503,0.1100668,0.01531756,0.5917343],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.2452053,"threshold_uncertainty_score":0.8525723,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03467398594823993,"score_gpt":0.2936418968347249,"score_spread":0.258967910886485,"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."}}