{"id":"W2011287359","doi":"10.1038/nmeth.1424","title":"Computational prediction of neural progenitor cell fates","year":2010,"lang":"en","type":"article","venue":"Nature Methods","topic":"Retinal Development and Disorders","field":"Biochemistry, Genetics and Molecular Biology","cited_by":114,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University; Université de Montréal; Montreal Clinical Research Institute","funders":"Canadian Institutes of Health Research","keywords":"Progenitor cell; Biology; Stem cell; Cell fate determination; Computational biology; Cell division; Computer science; Progenitor; Identification (biology); Cell biology; Cell; Genetics; Gene","routes":{"ca_aff":true,"ca_fund":true,"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":[],"consensus_categories":[],"category_scores_codex":[0.0002157826,0.000068126,0.0000648225,0.00002652523,0.00002775195,0.000006155174,0.00008371335,0.0002369231,0.00001831127],"category_scores_gemma":[0.0001105072,0.00005870289,0.00004853325,0.00006026914,0.00004024198,0.000001993426,0.00002945216,0.0002036859,9.330695e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000001351463,"about_ca_system_score_gemma":0.00003556379,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001027422,"about_ca_topic_score_gemma":0.000001010946,"domain_scores_codex":[0.9995331,0.00005683289,0.0001074265,0.0001381582,0.00008477033,0.00007968188],"domain_scores_gemma":[0.9997146,0.00002105469,0.00005010151,0.00008913201,0.00009632939,0.00002880831],"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":[0.00003633163,0.00003023199,0.01404269,0.00001539313,0.00001153136,1.989937e-7,0.00001914088,0.00004826723,0.9761949,0.00009073425,0.00107995,0.008430642],"study_design_scores_gemma":[0.0003068558,0.00008999762,0.03688619,0.000001752067,0.00001048564,0.00000551336,0.0000192042,0.0008102538,0.9344575,0.0006229646,0.02670658,0.00008273119],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9830558,0.0005174383,0.01275558,0.00008437088,0.0007171573,0.0001137689,0.00001325579,0.00001050721,0.002732104],"genre_scores_gemma":[0.7361618,0.000006138127,0.2633365,0.00006111075,0.0001135386,0.000005053158,0.0001226226,0.00000620828,0.0001870542],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2505809,"threshold_uncertainty_score":0.2393834,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006090576339896629,"score_gpt":0.3155458795675906,"score_spread":0.309455303227694,"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."}}