{"id":"W3115205064","doi":"","title":"Assessing a MOP to Cleanly Sweep Astronomical Images","year":2007,"lang":"en","type":"article","venue":"Journal of the Royal Astronomical Society of Canada","topic":"Astronomical Observations and Instrumentation","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Remote sensing; Computer science; Environmental science; Geology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"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":[0.001819219,0.0005672924,0.000553849,0.001728317,0.0005507667,0.001422201,0.0007305713,0.00136955,0.003381737],"category_scores_gemma":[0.01184137,0.0003213805,0.0004996003,0.0008176484,0.0003267649,0.001792801,0.001589799,0.000818339,0.001083366],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004139196,"about_ca_system_score_gemma":0.001042007,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007877672,"about_ca_topic_score_gemma":0.01266356,"domain_scores_codex":[0.9991339,0.0001450637,0.00005360958,0.0001834832,0.0003786543,0.0001053219],"domain_scores_gemma":[0.9963087,0.001498645,0.0003098111,0.0004063359,0.001201575,0.0002747682],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001535706,0.0003095272,0.05981259,0.0003473519,0.0004862991,0.0002539965,0.0002826584,0.04317423,0.1273651,0.001897082,0.007714627,0.756821],"study_design_scores_gemma":[0.0001411503,0.0007872054,0.1230016,0.00006222659,0.0003180195,0.0005195957,0.0004514632,0.7988446,0.06431543,0.003269387,0.008205192,0.00008414175],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5015548,0.0005178613,0.479034,0.001012182,0.0001745367,0.0004275607,0.002092259,0.008143459,0.007043327],"genre_scores_gemma":[0.6927224,0.0001749958,0.3030703,0.0001886381,0.000054428,0.00006935982,0.001392775,0.0004355127,0.001891614],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007877672,"threshold_uncertainty_score":0.01566362,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006937445279077679,"score_gpt":0.2068101735049258,"score_spread":0.1998727282258481,"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."}}