{"id":"W3032178258","doi":"","title":"Interpretable Contrastive Learning for Networks.","year":2020,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Bioinformatics and Genomic Networks","field":"Biochemistry, Genetics and Molecular Biology","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Interpretability; Computer science; Artificial intelligence; Representation (politics); Machine learning; Space (punctuation); Theoretical 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":[0.006867966,0.00184527,0.0008546598,0.0027782,0.0007207577,0.002271026,0.002077967,0.002233112,0.003696223],"category_scores_gemma":[0.02836838,0.0007542497,0.001463598,0.001398337,0.002637765,0.004178943,0.003155227,0.004748381,0.0008534127],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002498531,"about_ca_system_score_gemma":0.001022576,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001377687,"about_ca_topic_score_gemma":0.00218771,"domain_scores_codex":[0.9967866,0.001837073,0.0001270763,0.0006110898,0.0005543021,0.00008387077],"domain_scores_gemma":[0.985578,0.01109719,0.0009482735,0.001379289,0.0007774195,0.0002198323],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001684199,0.0001226724,0.001883437,0.0004591985,0.0001840458,0.0001967899,0.0003193535,0.3157807,0.0036457,0.4838358,0.008896648,0.1845072],"study_design_scores_gemma":[0.00001224209,0.00002437228,0.0001270939,0.00003215343,0.00001065047,0.00003793571,0.00001742991,0.7161212,0.0008579008,0.2802491,0.00250207,0.000007838943],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001811313,0.0003336915,0.9955604,0.0004564401,0.00003569632,0.000048631,0.0001538332,0.0003656302,0.001234446],"genre_scores_gemma":[0.2096779,0.0008351806,0.7835057,0.0005840691,0.0002665285,0.0006690499,0.001254794,0.000343863,0.002863054],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.006867966,"threshold_uncertainty_score":0.0363217,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03209538251877023,"score_gpt":0.1777387160184885,"score_spread":0.1456433334997183,"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."}}