{"id":"W3157763047","doi":"","title":"Creating A Fitting Algorithm for Exoplanet Detection","year":2018,"lang":"en","type":"article","venue":"URSCA Proceedings","topic":"Stellar, planetary, and galactic studies","field":"Physics and Astronomy","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"MacEwan University","funders":"","keywords":"Exoplanet; Telescope; Transit (satellite); Stars; Planet; Computer science; Identification (biology); Physics; Astronomy; Engineering","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014526,0.0001493918,0.0001623194,0.00004631764,0.0004292073,0.00007894495,0.00008190585,0.00003824958,0.0001211747],"category_scores_gemma":[0.00002851868,0.0001402273,0.00005530279,0.0001001254,0.00005284194,0.0001234585,0.00002776984,0.00008214326,0.0000447647],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001378687,"about_ca_system_score_gemma":0.00001074802,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001277205,"about_ca_topic_score_gemma":0.000003022735,"domain_scores_codex":[0.999164,0.000002519179,0.0001674275,0.0002554716,0.0001069166,0.0003036795],"domain_scores_gemma":[0.999518,0.00009722522,0.0001168519,0.00004949711,0.000165445,0.00005301891],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002730759,0.00003550575,0.5447521,0.00003472548,0.0001357226,2.339985e-7,0.002415596,2.558136e-7,0.0003713382,0.0004650457,0.004596398,0.4471658],"study_design_scores_gemma":[0.007323085,0.003364871,0.3678107,0.0005338736,0.001152809,0.00009130581,0.01804324,0.1544611,0.1537569,0.01775883,0.2724347,0.003268641],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.3215871,0.0001730751,0.05276076,0.0001876665,0.00132099,0.001012266,0.00004096329,0.0003036433,0.6226135],"genre_scores_gemma":[0.9860869,0.00000159413,0.009384774,0.00005214366,0.003463201,0.00005206853,0.00002200407,0.00002029572,0.0009169956],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6644998,"threshold_uncertainty_score":0.5718304,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01189087949293133,"score_gpt":0.2344134010888487,"score_spread":0.2225225215959174,"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."}}