{"id":"W3185688577","doi":"","title":"CANUCS: The CAnadian NIRISS Unbiased Cluster Survey","year":2017,"lang":"en","type":"article","venue":"JWST Proposal. Cycle 1","topic":"Advanced Clustering Algorithms Research","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Cluster (spacecraft); Computer science","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":[0.0219465,0.001742857,0.001771922,0.008221217,0.00750998,0.006207407,0.006018228,0.001705109,0.03288568],"category_scores_gemma":[0.05270435,0.001023301,0.001094959,0.013613,0.001840238,0.002057345,0.006003507,0.002671659,0.01693045],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.02681537,"about_ca_system_score_gemma":0.115906,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9255908,"about_ca_topic_score_gemma":0.9518062,"domain_scores_codex":[0.9869276,0.002502886,0.0002642223,0.001311872,0.00676811,0.002225281],"domain_scores_gemma":[0.9597756,0.003019884,0.0008530564,0.0062057,0.02638683,0.003758793],"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":[0.0001885792,0.00004147991,0.007300941,0.0001701909,0.00008955911,0.00002561804,0.0001990939,0.001980604,0.000332048,0.01493056,0.9140272,0.06071421],"study_design_scores_gemma":[0.0001771131,0.00004873566,0.03150373,0.0003029747,0.00009465945,0.00005848714,0.0006381362,0.008853509,0.00147326,0.01340516,0.9433063,0.000138003],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.02105575,0.005238423,0.1742883,0.02443998,0.004455016,0.003635304,0.5353786,0.01850661,0.213002],"genre_scores_gemma":[0.1013034,0.003937255,0.1823829,0.008333412,0.001574182,0.004423329,0.5187561,0.009624153,0.1696652],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.07440919,"threshold_uncertainty_score":0.1945601,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03733052967814782,"score_gpt":0.3260834764864209,"score_spread":0.2887529468082731,"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."}}