{"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":"codex-gemma-dda1882f352a","candidate_categories":["sts","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.001652886,0.0002184764,0.0002036576,0.0001197232,0.00254113,0.001772546,0.004697322,0.0001158315,0.00003320433],"category_scores_gemma":[0.0007360054,0.0001587274,0.00006503519,0.0002210139,0.0003793325,0.0008485144,0.001127215,0.000499869,0.000432599],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003833527,"about_ca_system_score_gemma":0.001427671,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.4519361,"about_ca_topic_score_gemma":0.7851688,"domain_scores_codex":[0.9972717,0.0003278801,0.0002410209,0.0005989391,0.0006371684,0.0009233569],"domain_scores_gemma":[0.9960068,0.0001556279,0.0001530304,0.002934506,0.0002874275,0.0004625594],"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":[0.0001791863,0.0004106072,0.08961783,0.0001890011,0.0003618865,0.001260847,0.006848809,0.005926017,0.0008607086,0.02575863,0.06389883,0.8046876],"study_design_scores_gemma":[0.001360486,0.0001759098,0.5990595,0.00006655126,0.0000091293,0.00008994632,0.0000558767,0.3424179,0.001450736,0.007271589,0.04709463,0.0009477816],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1911689,0.0004818562,0.4762704,0.2159311,0.009605465,0.006987861,0.0003934665,0.001632988,0.09752801],"genre_scores_gemma":[0.9779298,0.000008178882,0.01727327,0.0007371557,0.0002046083,0.00006217277,0.000009007137,0.00003726125,0.003738538],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8037398,"threshold_uncertainty_score":0.9992637,"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."}}