{"id":"W4400798919","doi":"10.1101/2024.07.15.603557","title":"COLLAGE: COnsensus aLignment of muLtiplexing imAGEs","year":2024,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Single-cell and spatial transcriptomics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dynamic Systems Analysis (Canada)","funders":"","keywords":"Multiplexing; Computer science; Artificial intelligence; Computer vision; Telecommunications","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003755853,0.0005079122,0.0005043478,0.0001387959,0.00007590452,0.0001006519,0.0004299616,0.0006240395,0.00001612613],"category_scores_gemma":[0.0001339223,0.0005444001,0.0002777898,0.0001802312,0.0002194756,0.000001977234,0.000639057,0.000425244,0.00002066801],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007610273,"about_ca_system_score_gemma":0.0005393508,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007673544,"about_ca_topic_score_gemma":0.00000412839,"domain_scores_codex":[0.9976499,0.000100376,0.0005871871,0.0009539425,0.0002824847,0.0004260915],"domain_scores_gemma":[0.9981696,0.00002705775,0.0002708347,0.001016958,0.0003402266,0.0001753456],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00006938693,0.0001230045,0.001588008,0.0007356352,0.0002925007,0.0000390367,0.000006999559,0.0001926106,0.9954399,0.0001147657,0.001395708,0.000002399734],"study_design_scores_gemma":[0.0004814189,0.0001045501,0.002287642,0.0003499045,0.0001335093,3.521983e-8,0.000004429063,0.0001978221,0.9900958,0.000003735519,0.005767754,0.0005733843],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9903492,0.005415729,0.0006862615,0.0001554552,0.001751094,0.0005655367,0.0009206692,0.0001104443,0.00004556743],"genre_scores_gemma":[0.9935952,0.0004194673,0.005098068,0.0001137162,0.0005239935,0.00007174776,0.000002247553,0.000143732,0.00003179467],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005344129,"threshold_uncertainty_score":0.9997007,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01316894121997493,"score_gpt":0.2228480545582998,"score_spread":0.2096791133383249,"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."}}