{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003779115,0.002451672,0.001549904,0.003182546,0.001450926,0.003149099,0.0034999,0.001784596,0.05770463],"category_scores_gemma":[0.007488888,0.001542715,0.001271171,0.001868173,0.001090765,0.002082258,0.004262195,0.002860404,0.02010777],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001222317,"about_ca_system_score_gemma":0.001986086,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001977609,"about_ca_topic_score_gemma":0.002803385,"domain_scores_codex":[0.9963948,0.0005097307,0.0002224575,0.001191901,0.001369789,0.000311315],"domain_scores_gemma":[0.9972651,0.0005707028,0.000317914,0.0009433162,0.0006321286,0.0002708617],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001599282,0.0002007355,0.001835739,0.0008772931,0.0003789543,0.0004965115,0.0004813011,0.01403491,0.1791472,0.02210111,0.2164082,0.5624387],"study_design_scores_gemma":[0.0002311397,0.0003060953,0.002359404,0.000158627,0.00007171198,0.0005464383,0.0002985815,0.4681129,0.3570335,0.02602816,0.1445186,0.0003350165],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.008375086,0.0002951099,0.8816975,0.0003814256,0.0004883879,0.0004448787,0.002954948,0.09960003,0.005762514],"genre_scores_gemma":[0.04734927,0.000173135,0.9311758,0.0002983242,0.0001267207,0.0008311478,0.003965196,0.01097917,0.005101198],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.05770463,"threshold_uncertainty_score":0.1930412,"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."}}