{"id":"W6931132694","doi":"10.5281/zenodo.2561098","title":"juliema/aTRAM: Improve aTRAM stability","year":2019,"lang":"en","type":"other","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Biological Stains and Phytochemicals","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Stability (learning theory); Footprint; Complete information; Task (project management); Key (lock); Term (time)","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":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0004198445,0.000263484,0.0004232735,0.0001263355,0.0003398764,0.0001642265,0.0006050196,0.0004033377,0.1040058],"category_scores_gemma":[0.0005164515,0.0002182796,0.0001414856,0.0002871337,0.0002451943,0.00003511824,0.0007531981,0.0007032602,0.01877025],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001547546,"about_ca_system_score_gemma":0.000008671141,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002754302,"about_ca_topic_score_gemma":2.085479e-7,"domain_scores_codex":[0.9980361,0.0001801837,0.0002905925,0.0006749879,0.0003708607,0.0004473013],"domain_scores_gemma":[0.99841,0.00002434195,0.000164264,0.0008304113,0.0002778248,0.0002931141],"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":[0.000116799,0.0001999317,0.000006286228,0.0004662413,0.0000919098,0.00001205634,0.00007440647,1.268422e-7,0.009309145,0.0008215455,0.9315801,0.05732146],"study_design_scores_gemma":[0.0006537928,0.0005390855,0.000138333,0.0001149733,0.00004544709,0.00003415067,0.00004948506,0.00001329453,0.0007057961,0.00009459717,0.9973711,0.0002399078],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.0007068691,0.0004379344,0.0003584079,0.0006830221,0.0001657228,0.001410313,0.0008081977,0.001223509,0.994206],"genre_scores_gemma":[0.09471484,0.001064331,0.0009373425,0.001333816,0.002341111,2.868075e-7,0.012411,0.01985766,0.8673396],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.1268664,"threshold_uncertainty_score":0.9819937,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04209964733934837,"score_gpt":0.2666637956346556,"score_spread":0.2245641482953072,"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."}}