{"id":"W1924089270","doi":"10.1093/mnras/stv2009","title":"Space Warps – I. Crowdsourcing the discovery of gravitational lenses","year":2015,"lang":"en","type":"article","venue":"Monthly Notices of the Royal Astronomical Society","topic":"Galaxies: Formation, Evolution, Phenomena","field":"Physics and Astronomy","cited_by":114,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Crowdsourcing; Physics; Lens (geology); Scalability; Sample (material); Projection (relational algebra); Computer vision; Artificial intelligence; Set (abstract data type); Computer science; Optics; Algorithm; World Wide Web","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":[0.002390752,0.0009509655,0.0008798187,0.001512676,0.001482301,0.002098325,0.001646905,0.001096206,0.007820191],"category_scores_gemma":[0.00803008,0.0004745819,0.0008556817,0.002191859,0.00119588,0.001954871,0.004375032,0.001141112,0.00670502],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001217732,"about_ca_system_score_gemma":0.001461111,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01932851,"about_ca_topic_score_gemma":0.02470879,"domain_scores_codex":[0.996954,0.0006530322,0.0001084367,0.0006771111,0.001302654,0.0003048267],"domain_scores_gemma":[0.995788,0.001098145,0.0002872165,0.001703374,0.0005906927,0.0005325173],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.001754007,0.0003168398,0.02921894,0.001223128,0.0003494953,0.001025458,0.004489994,0.02955082,0.03696381,0.02657022,0.3246962,0.5438411],"study_design_scores_gemma":[0.0002634687,0.0004186675,0.02696764,0.0002565654,0.0000701087,0.001059945,0.002655938,0.2172413,0.02913605,0.06144391,0.6601328,0.0003537142],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1739733,0.003524875,0.5371734,0.008957672,0.002149464,0.003243559,0.05983054,0.07968928,0.131458],"genre_scores_gemma":[0.5556051,0.001094383,0.350843,0.002399847,0.00114604,0.001600891,0.03915503,0.004931761,0.04322404],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01932851,"threshold_uncertainty_score":0.038432,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01011681111028867,"score_gpt":0.2048243329535998,"score_spread":0.1947075218433111,"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."}}