{"id":"W1990127492","doi":"10.1155/2015/689745","title":"Shaped Singular Spectrum Analysis for Quantifying Gene Expression, with Application to the Early<i>Drosophila</i>Embryo","year":2015,"lang":"en","type":"article","venue":"BioMed Research International","topic":"Statistical and numerical algorithms","field":"Mathematics","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"British Columbia Institute of Technology","funders":"National Institute of General Medical Sciences; Dynasty Foundation; National Institutes of Health; Russian Foundation for Basic Research","keywords":"Drosophila (subgenus); Embryo; Computational biology; Biology; Gene expression; Gene; Expression (computer science); Drosophila melanogaster; Ellipsoid; Projection (relational algebra); Noise (video); Computer science; Image (mathematics); Pattern recognition (psychology); Genetics; Bioinformatics; Artificial intelligence; Algorithm; Physics","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":[],"consensus_categories":[],"category_scores_codex":[0.00142098,0.0001282978,0.0001994723,0.0003865565,0.0002183063,0.0001468187,0.0006159015,0.00005604094,0.00006822323],"category_scores_gemma":[0.001371511,0.00007598176,0.00008959573,0.001304644,0.0001427293,0.00007487011,0.0001766413,0.0001819439,0.00008924445],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001423935,"about_ca_system_score_gemma":0.00007236536,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001656627,"about_ca_topic_score_gemma":0.0000464294,"domain_scores_codex":[0.9973958,0.0001234108,0.0002858062,0.0004004798,0.001399646,0.000394857],"domain_scores_gemma":[0.9976077,0.000920765,0.00007717899,0.0003496719,0.0007474722,0.0002972154],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.006338421,0.003608174,0.01950701,0.0002374314,0.006058899,0.0001191828,0.005301933,0.0006479419,0.3244485,0.4979422,0.1054829,0.03030739],"study_design_scores_gemma":[0.003832392,0.001628903,0.02643042,0.0001088908,0.0003738519,0.00002986332,0.0008710171,0.3016606,0.04227788,0.5078222,0.113938,0.001025996],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03203331,0.00002921915,0.9554563,0.01109827,0.0001981023,0.0007307537,0.0001414063,0.00005188913,0.00026072],"genre_scores_gemma":[0.8079609,0.000004834108,0.189043,0.0001539005,0.0008847918,0.0006159773,0.0001367326,0.00003329264,0.001166549],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.7759275,"threshold_uncertainty_score":0.3098446,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2033304373450711,"score_gpt":0.4343569648856764,"score_spread":0.2310265275406052,"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."}}