{"id":"W6891637820","doi":"10.48550/arxiv.1504.06148","title":"Space Warps: I. Crowd-sourcing the Discovery of Gravitational Lenses","year":2015,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Astronomy and Astrophysical Research","field":"Physics and Astronomy","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Lens (geology); Scalability; Sample (material); Set (abstract data type); Field of view; Projection (relational algebra); Gravitational lens; Sky; Image (mathematics)","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":[0.004272792,0.001178849,0.001167972,0.002131752,0.0015924,0.003187231,0.002078439,0.001445159,0.004124092],"category_scores_gemma":[0.009455779,0.0006433753,0.0009621625,0.002328393,0.00153295,0.002817493,0.00585554,0.001442757,0.003364565],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001319674,"about_ca_system_score_gemma":0.001294798,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.012911,"about_ca_topic_score_gemma":0.01640297,"domain_scores_codex":[0.9965813,0.0008415436,0.0001341732,0.0007316382,0.001234617,0.0004769138],"domain_scores_gemma":[0.9953778,0.001342958,0.0004138923,0.001471265,0.0006220067,0.000772162],"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":[0.003047094,0.0005411641,0.1134383,0.001323479,0.0006705288,0.002638733,0.01302691,0.03697553,0.0452186,0.03791131,0.252542,0.4926663],"study_design_scores_gemma":[0.000382916,0.0009630696,0.05486725,0.0003655455,0.0001606761,0.003382958,0.00712256,0.3496807,0.04798071,0.05766894,0.4768712,0.0005536322],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4101875,0.0050879,0.4267189,0.008076491,0.001850933,0.002519965,0.03357163,0.05230356,0.05968321],"genre_scores_gemma":[0.6100556,0.001050571,0.3420271,0.001769278,0.001190865,0.0009068461,0.0239758,0.00300512,0.01601876],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.012911,"threshold_uncertainty_score":0.02567166,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06721686015050347,"score_gpt":0.2198561663579885,"score_spread":0.152639306207485,"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."}}