{"id":"W7095746214","doi":"","title":"Astronomy &amp;amp; Astrophysics manuscript no. (will be inserted by hand later) Cosmic Shear Analysis with CFHTLS Deep data ⋆","year":2006,"lang":"en","type":"article","venue":"","topic":"Galaxies: Formation, Evolution, Phenomena","field":"Physics and Astronomy","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Weak gravitational lensing; Galaxy; Halo; Amplitude; Dark matter; Redshift; COSMIC cancer database; Cold dark matter","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002000573,0.0005247782,0.0003525922,0.004081567,0.0007293594,0.001953488,0.0008665208,0.0004155958,0.1734045],"category_scores_gemma":[0.007821186,0.0003214019,0.0002860233,0.004023231,0.0005056922,0.0009642315,0.001534521,0.000708739,0.115137],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008395024,"about_ca_system_score_gemma":0.001308274,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006033983,"about_ca_topic_score_gemma":0.006950303,"domain_scores_codex":[0.9992123,0.00006942931,0.00005937228,0.0001431447,0.0004005961,0.0001151728],"domain_scores_gemma":[0.993205,0.0008895137,0.0007635501,0.002029113,0.002092392,0.001020477],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.000112247,0.0000365206,0.01503912,0.0002393934,0.00002924536,0.0001203031,0.0001364592,0.0004423574,0.002258515,0.008629155,0.8620294,0.1109273],"study_design_scores_gemma":[0.00002004301,0.00002284262,0.02694011,0.00003795128,0.000007128767,0.00007897576,0.00003622048,0.0004107073,0.001775414,0.0023513,0.9683053,0.00001403128],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.0185499,0.0006662168,0.0124147,0.003398133,0.003027563,0.0004445261,0.5019899,0.007771801,0.4517373],"genre_scores_gemma":[0.1302334,0.001016959,0.0329974,0.001238254,0.00182097,0.0005841911,0.475687,0.006092986,0.3503289],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.1734045,"threshold_uncertainty_score":0.5800956,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01269452446175268,"score_gpt":0.211136266767267,"score_spread":0.1984417423055143,"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."}}