{"id":"W4389903258","doi":"10.1101/2023.12.18.572148","title":"RASP: Optimal single fluorescent puncta detection in complex cellular backgrounds","year":2023,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Fluorescence Microscopy Techniques","field":"Biochemistry, Genetics and Molecular Biology","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Polytechnique Montréal; Centre for Movement Disorders","funders":"Medical Research Council; Michael J. Fox Foundation for Parkinson's Research","keywords":"Segmentation; Biology; Phenotype; Biological system; Computer science; Computational biology; Cell biology; Artificial intelligence; Genetics; Gene","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":[0.0006261011,0.0007838174,0.0006782978,0.0007012358,0.0004150089,0.0009130238,0.001069805,0.0008133306,0.001873258],"category_scores_gemma":[0.001024035,0.0005734149,0.0004265639,0.0004788721,0.0006808183,0.0007898558,0.001293474,0.0008955905,0.001588716],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005889646,"about_ca_system_score_gemma":0.0006691808,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001144724,"about_ca_topic_score_gemma":0.001314104,"domain_scores_codex":[0.9995988,0.00006207904,0.00001659053,0.000104886,0.0001580768,0.00005957695],"domain_scores_gemma":[0.9997153,0.00009103474,0.00004322432,0.00006529149,0.00005075633,0.00003440751],"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":[0.0005912202,0.00009208898,0.001150173,0.0002532709,0.0000570292,0.0003413635,0.0001255601,0.04437377,0.7731329,0.01455915,0.005823517,0.1594999],"study_design_scores_gemma":[0.0000325868,0.00005618699,0.001066356,0.00001044139,0.00001226639,0.0003649732,0.00002813225,0.6240687,0.3605483,0.008025758,0.005749697,0.0000365901],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.06654976,0.0002291741,0.9201452,0.0002352778,0.00004110867,0.00005829663,0.0003403407,0.01030859,0.002092249],"genre_scores_gemma":[0.2930183,0.0004102605,0.6990287,0.0001034805,0.00003816134,0.0001826918,0.000665608,0.002228633,0.004324101],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.001873258,"threshold_uncertainty_score":0.006266654,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02297618423830006,"score_gpt":0.2503107470220974,"score_spread":0.2273345627837973,"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."}}