{"id":"W2069122147","doi":"10.1088/2041-8205/733/2/l30","title":"LENSING MAGNIFICATION: A NOVEL METHOD TO WEIGH HIGH-REDSHIFT CLUSTERS AND ITS APPLICATION TO SpARCS","year":2011,"lang":"en","type":"article","venue":"The Astrophysical Journal Letters","topic":"Galaxies: Formation, Evolution, Phenomena","field":"Physics and Astronomy","cited_by":46,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; University of British Columbia","funders":"","keywords":"Redshift; Physics; Astrophysics; Galaxy; Galaxy cluster; Weak gravitational lensing; Sigma; Cluster (spacecraft); Photometric redshift; Astronomy; Computer science","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":[0.0005210626,0.000571646,0.0003070257,0.001894827,0.0003987707,0.0008817582,0.000727254,0.0002689378,0.004082186],"category_scores_gemma":[0.001463665,0.0003264983,0.0003224245,0.001562314,0.0004085355,0.000923815,0.0009884867,0.0004454489,0.0008551886],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004493433,"about_ca_system_score_gemma":0.0002736948,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003814911,"about_ca_topic_score_gemma":0.00486325,"domain_scores_codex":[0.9995944,0.00003626178,0.00001564925,0.0001111607,0.0002043426,0.00003827371],"domain_scores_gemma":[0.9993333,0.0001066268,0.0001250586,0.000183393,0.0001912947,0.00006024655],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002697681,0.00006321402,0.08725817,0.0002452026,0.0003485348,0.0005005656,0.0005832562,0.02586091,0.1398468,0.04324049,0.00822866,0.6935544],"study_design_scores_gemma":[0.00009939327,0.0003968698,0.2732911,0.00008222392,0.0001954369,0.003011525,0.0003602406,0.4079131,0.1460695,0.05029639,0.1179184,0.0003658661],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1645446,0.0007718562,0.8040121,0.0002037829,0.0002011901,0.0001828338,0.001777269,0.006758067,0.02154833],"genre_scores_gemma":[0.4776771,0.0004298207,0.5118359,0.0001427398,0.0002648543,0.0001814641,0.001383636,0.0008094496,0.007275071],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004082186,"threshold_uncertainty_score":0.01365626,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0149600147646936,"score_gpt":0.2276635631966328,"score_spread":0.2127035484319392,"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."}}