{"id":"W2530211828","doi":"10.1093/mnras/stw2606","title":"Pattern recognition in the ALFALFA.70 and Sloan Digital Sky Surveys: a catalogue of ∼500 000 H i gas fraction estimates based on artificial neural networks","year":2016,"lang":"en","type":"article","venue":"Monthly Notices of the Royal Astronomical Society","topic":"Galaxies: Formation, Evolution, Phenomena","field":"Physics and Astronomy","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"Trent University; University of Victoria","funders":"","keywords":"Physics; Sky; Galaxy; Surface brightness; Astrophysics; Stellar mass; Mass fraction; Star formation; Bulge; Galaxy formation and evolution; Artificial neural network; Artificial intelligence","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":[0.0004950796,0.0004823113,0.0003278277,0.00261247,0.0001955697,0.0006018078,0.0004440461,0.0002513058,0.000741748],"category_scores_gemma":[0.001406125,0.0001638617,0.0005054607,0.002321736,0.0001569979,0.0002969763,0.0003591478,0.0001826243,0.0006599875],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005877376,"about_ca_system_score_gemma":0.0005562646,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04451319,"about_ca_topic_score_gemma":0.04369653,"domain_scores_codex":[0.9996787,0.00005193966,0.0000356273,0.00007176591,0.000131184,0.00003075006],"domain_scores_gemma":[0.9991974,0.0001402811,0.0001793167,0.0001925494,0.000230157,0.00006032033],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002149615,0.000130953,0.6145779,0.0002882185,0.0002844352,0.0003235651,0.0002255019,0.02965864,0.00607989,0.001050691,0.03083291,0.3163323],"study_design_scores_gemma":[0.0000195205,0.00004981436,0.9189059,0.00004838129,0.00004500665,0.0001644273,0.0001396311,0.05989668,0.002254513,0.000724749,0.01773065,0.00002073245],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9339694,0.001413517,0.01628365,0.0002268123,0.00002717217,0.00007322815,0.0392021,0.002435313,0.006368762],"genre_scores_gemma":[0.8520119,0.0009812564,0.03130913,0.00008168118,0.00001864405,0.0001327156,0.1112568,0.0001246162,0.004083199],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04451319,"threshold_uncertainty_score":0.08850819,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01012328792782954,"score_gpt":0.1964265491993345,"score_spread":0.186303261271505,"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."}}