{"id":"W7027892469","doi":"","title":"Dum Dums - S02 E16 Project: Under Gardiner","year":2016,"lang":"en","type":"other","venue":"Bulletin of Miscellaneous Information (Royal Gardens Kew)","topic":"Metaheuristic Optimization Algorithms Research","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Downtown; Space (punctuation); Public space; Selection (genetic algorithm)","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":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.001885416,0.0009698522,0.00059748,0.001070739,0.001633747,0.005061209,0.001370205,0.001568349,0.4660582],"category_scores_gemma":[0.003108301,0.0004100468,0.0004527425,0.001269705,0.0006579637,0.002029467,0.002989712,0.001435194,0.334662],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002482799,"about_ca_system_score_gemma":0.00439557,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02348216,"about_ca_topic_score_gemma":0.04207624,"domain_scores_codex":[0.9987656,0.0001884603,0.00002333111,0.0002488687,0.0005208381,0.0002528201],"domain_scores_gemma":[0.9969193,0.0001538675,0.00007805417,0.0003379216,0.001228481,0.001282418],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000179053,0.00009325452,0.0003370612,0.0001040641,0.000005097672,0.00005536598,0.00008521137,0.0001864065,0.0009575494,0.00584161,0.932059,0.06009622],"study_design_scores_gemma":[0.00002303269,0.00003689986,0.0001995351,0.00001760099,0.000001404467,0.0000276418,0.00007393974,0.0002224805,0.0005251514,0.0004019833,0.9984661,0.000004326756],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.003415902,0.001076225,0.008289341,0.005534299,0.00239328,0.0005585943,0.01140294,0.01148382,0.9558456],"genre_scores_gemma":[0.01330653,0.0005872495,0.005396055,0.0006565824,0.000228932,0.000154947,0.01077804,0.003859221,0.9650324],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.5339417,"threshold_uncertainty_score":0.7616031,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01099736268798992,"score_gpt":0.2272728513831559,"score_spread":0.2162754886951659,"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."}}