{"id":"W3127522569","doi":"10.1242/dev.192955","title":"LAMA: automated image analysis for the developmental phenotyping of mouse embryos","year":2021,"lang":"en","type":"article","venue":"Development","topic":"Cell Image Analysis Techniques","field":"Biochemistry, Genetics and Molecular Biology","cited_by":20,"is_retracted":false,"has_abstract":true,"ca_institutions":"Hospital for Sick Children","funders":"National Human Genome Research Institute; National Institutes of Health","keywords":"Biology; Pipeline (software); Embryo; Segmentation; Computational biology; Bioinformatics; Artificial intelligence; Genetics; Computer science; Operating system","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":[0.001714622,0.001082345,0.0007737797,0.003055795,0.0007526234,0.001787143,0.002142184,0.0008632997,0.01319136],"category_scores_gemma":[0.002533294,0.0009270859,0.001140242,0.001106348,0.0005506066,0.0009967169,0.001697406,0.001378612,0.005859611],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008918951,"about_ca_system_score_gemma":0.001654236,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00207716,"about_ca_topic_score_gemma":0.004362345,"domain_scores_codex":[0.9991333,0.0001508403,0.00007677485,0.0001887043,0.000374539,0.00007579346],"domain_scores_gemma":[0.9988716,0.0004247431,0.0001630208,0.0002807234,0.0001876248,0.0000721626],"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":[0.0005046108,0.0001706559,0.004693964,0.000872866,0.0003396684,0.0004389088,0.0004334397,0.01493222,0.4156221,0.007346719,0.08480523,0.4698396],"study_design_scores_gemma":[0.0001424762,0.0002244639,0.02297516,0.000161416,0.0001207056,0.001586723,0.000157715,0.4510587,0.4109246,0.008619251,0.1037582,0.0002706091],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0121948,0.0001922036,0.8405264,0.0001713273,0.00003810311,0.0001853962,0.005557917,0.1392674,0.001866461],"genre_scores_gemma":[0.05295611,0.0002390599,0.924201,0.0001685508,0.00002484172,0.0009254607,0.007197642,0.01185178,0.002435615],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01319136,"threshold_uncertainty_score":0.04412955,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01010116279905076,"score_gpt":0.2635935161084831,"score_spread":0.2534923533094323,"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."}}