{"id":"W4323669103","doi":"10.1101/2023.03.05.531195","title":"Biological representation disentanglement of single-cell data","year":2023,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Single-cell and spatial transcriptomics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Council for Higher Education; Azrieli Foundation; European Commission","keywords":"Generalization; Computer science; Population; Expression (computer science); Computational biology; Representation (politics); Generative grammar; Artificial intelligence; Machine learning; Biology; Mathematics","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001228234,0.0005671354,0.000656385,0.001207819,0.0002580303,0.001245458,0.001265859,0.0009234141,0.001801391],"category_scores_gemma":[0.004013694,0.0004622924,0.001272113,0.001030884,0.0008464177,0.001000125,0.001800707,0.001664049,0.0005694235],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007662518,"about_ca_system_score_gemma":0.0007572474,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00352269,"about_ca_topic_score_gemma":0.004799005,"domain_scores_codex":[0.9995956,0.0000917031,0.00002435716,0.0001197321,0.000119215,0.00004957122],"domain_scores_gemma":[0.9985024,0.0008232393,0.0001380627,0.0003295964,0.0001198219,0.00008689511],"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":[0.0003697448,0.0001090899,0.01136893,0.0004182612,0.0002591471,0.0003917385,0.0003015957,0.7203693,0.06376603,0.03190519,0.006282819,0.1644581],"study_design_scores_gemma":[0.000008571318,0.0000259989,0.001701587,0.00001763564,0.00001728206,0.00006095968,0.00002706411,0.964291,0.008775908,0.0221299,0.002920992,0.00002300654],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06846011,0.0005617875,0.9236956,0.0004071169,0.00006751252,0.00004182204,0.00258925,0.00304245,0.001134425],"genre_scores_gemma":[0.7305703,0.0005772155,0.254623,0.0003970413,0.00008115932,0.0002084508,0.01036046,0.0007091481,0.002473285],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00352269,"threshold_uncertainty_score":0.00700438,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07626785439254832,"score_gpt":0.2675284545404145,"score_spread":0.1912606001478661,"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."}}