{"id":"W4385720512","doi":"10.3389/fspas.2023.1197358","title":"Efficient galaxy classification through pretraining","year":2023,"lang":"en","type":"article","venue":"Frontiers in Astronomy and Space Sciences","topic":"Galaxies: Formation, Evolution, Phenomena","field":"Physics and Astronomy","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"Natural Sciences and Engineering Research Council of Canada; Alliance de recherche numérique du Canada; Simon Fraser University","keywords":"Physics; Galaxy; Convolutional neural network; Sky; Artificial intelligence; Astrophysics; Galaxy formation and evolution; Pattern recognition (psychology); Computer science","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":[0.0005585765,0.0001319931,0.0001507082,0.0002094425,0.0003840059,0.0001041163,0.0001888577,0.00002787034,0.00004595561],"category_scores_gemma":[0.000009263736,0.0001261181,0.00003606639,0.0008461252,0.0004015149,0.0003144953,0.00005283458,0.000111731,0.00002751567],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004769232,"about_ca_system_score_gemma":0.00009953084,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005813758,"about_ca_topic_score_gemma":0.000003431799,"domain_scores_codex":[0.9988087,0.00004656348,0.0002157416,0.0003256128,0.0002060823,0.0003972869],"domain_scores_gemma":[0.9996402,0.00002962271,0.0001134435,0.0001331235,0.00002464054,0.00005902391],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00000271838,0.00001425752,0.9785078,0.000003996524,0.00000705569,4.82354e-9,0.002737742,0.002215046,0.00001163788,0.01260056,0.001532939,0.002366197],"study_design_scores_gemma":[0.0002205735,0.00002926004,0.8998786,0.00001699852,0.000004285699,1.619641e-7,0.02074519,0.07395511,0.00002667755,0.003544381,0.001447972,0.0001307931],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9389469,0.00006527472,0.05580751,0.0004751572,0.0004813803,0.0001894975,0.000006502604,0.00005334883,0.003974426],"genre_scores_gemma":[0.9566596,0.000004174978,0.04286987,0.000001482696,0.00009151803,0.0000382066,0.00001522882,0.000005864512,0.0003141017],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07862926,"threshold_uncertainty_score":0.5142948,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01750100793306008,"score_gpt":0.2409585794344362,"score_spread":0.2234575715013762,"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."}}