{"id":"W3019840641","doi":"","title":"Automatic Approach to Morphological Classification of Galaxies with Analysis of Galaxy Populations in Clusters","year":2018,"lang":"en","type":"article","venue":"UND Scholarly Commons (University of North Dakota)","topic":"Optics and Image Analysis","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Galaxy; Supercluster (genetic); Computer science; Artificial intelligence; Astrophysics; Pattern recognition (psychology); Physics; Biology; Phylogenetics; Genetics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002562526,0.000104527,0.0003946194,0.001646634,0.0001445266,0.00008078154,0.0003828663,0.00004881376,0.00009739629],"category_scores_gemma":[0.00007198312,0.0001054171,0.0001322403,0.004227033,0.0002094572,0.001542604,0.0001607709,0.0001112214,0.00001088594],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002933594,"about_ca_system_score_gemma":0.00002004918,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002334418,"about_ca_topic_score_gemma":0.01703184,"domain_scores_codex":[0.9990987,0.00002853798,0.0002436993,0.0002152064,0.0002782518,0.0001356134],"domain_scores_gemma":[0.9986203,0.00002747711,0.0003555534,0.0003895432,0.0005863978,0.00002069981],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00003722042,0.0002133285,0.9954757,0.00003825165,0.0003138439,0.000001801507,0.0001657298,0.0009429054,0.00008106124,0.00182166,0.00009547744,0.0008130196],"study_design_scores_gemma":[0.0002458355,0.00003709496,0.8905897,0.00001798,0.001092411,1.908574e-7,0.0006193011,0.1071664,0.000001533237,0.00004611805,0.00008503045,0.00009849647],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9856423,0.000007759627,0.008788501,0.0002512385,0.00001152326,0.0001362253,0.00001177582,0.0000172873,0.005133375],"genre_scores_gemma":[0.9903682,0.000001578077,0.009421943,0.00002234765,0.00001291025,4.134045e-7,0.000106192,0.000005736968,0.00006062551],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1062235,"threshold_uncertainty_score":0.9504166,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04850671940993755,"score_gpt":0.2399939212707883,"score_spread":0.1914872018608507,"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."}}