{"id":"W4410907423","doi":"10.21428/d82e957c.4eb2f287","title":"SinSim: Sinkhorn-Regularized SimCLR","year":2025,"lang":"en","type":"article","venue":"","topic":"Glycosylation and Glycoproteins Research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003290111,0.001420507,0.001672596,0.00132732,0.0007222194,0.001453877,0.003616046,0.002379228,0.004739115],"category_scores_gemma":[0.005757872,0.0006434409,0.001704937,0.001117987,0.00135623,0.002298945,0.002848509,0.002651099,0.002415556],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00124831,"about_ca_system_score_gemma":0.001672504,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003073547,"about_ca_topic_score_gemma":0.005440485,"domain_scores_codex":[0.9985354,0.0004976528,0.00008294806,0.0003878339,0.0003921056,0.0001040672],"domain_scores_gemma":[0.9980736,0.0005502452,0.0001926137,0.0005855272,0.0004847432,0.000113328],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004324151,0.0003330392,0.002480004,0.0003921067,0.000253676,0.0002201297,0.0002128595,0.5163507,0.0162311,0.02874313,0.02714414,0.4072067],"study_design_scores_gemma":[0.00001528072,0.00003856956,0.00008014237,0.000008205116,0.000005738548,0.0000311167,0.000009078338,0.989183,0.002494243,0.006784376,0.001340579,0.000009719444],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01544925,0.0002455097,0.975365,0.0002481302,0.00006624935,0.000106009,0.0003000103,0.006608907,0.001611024],"genre_scores_gemma":[0.3082084,0.0002493477,0.6763005,0.0008654312,0.0001134077,0.0004504283,0.003339151,0.002708763,0.007764503],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.004739115,"threshold_uncertainty_score":0.01740003,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005294413929743159,"score_gpt":0.2865370183263187,"score_spread":0.2812426043965756,"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."}}