{"id":"W2338667702","doi":"10.1515/agms-2016-0016","title":"Constant Distortion Embeddings ofSymmetric Diversities","year":2016,"lang":"en","type":"preprint","venue":"Analysis and Geometry in Metric Spaces","topic":"Cell Adhesion Molecules Research","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Cardinality (data modeling); Distortion (music); Mathematics; Metric space; Embedding; Metric (unit); Constant (computer programming); Set (abstract data type); Space (punctuation); Combinatorics; Discrete mathematics; Pure mathematics; Computer science; Artificial intelligence; Telecommunications","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":["metaepi_narrow","bibliometrics"],"consensus_categories":[],"category_scores_codex":[0.001020554,0.0003401061,0.00125253,0.02120932,0.0000922539,0.0001375277,0.0002248012,0.0003710114,0.0007369986],"category_scores_gemma":[0.001312435,0.0002527551,0.0005094718,0.0152566,0.0002191602,0.00007478147,0.0008404556,0.0006369545,0.00003122645],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000383399,"about_ca_system_score_gemma":0.0001273718,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001281574,"about_ca_topic_score_gemma":0.000094749,"domain_scores_codex":[0.9969158,0.0001370647,0.0005325046,0.0008443606,0.001122202,0.0004480657],"domain_scores_gemma":[0.9978999,0.0006323059,0.0003172883,0.0005922001,0.0002842667,0.0002740402],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001415227,0.0001749598,0.9719627,0.0003725959,0.002505593,0.0002004803,0.0001407918,0.00003988916,0.0003269446,0.0001068729,0.000833275,0.02319433],"study_design_scores_gemma":[0.001668233,0.0003838319,0.9816259,0.0003380441,0.00623477,0.00001524047,0.0016819,0.00195706,0.001687768,0.0008636075,0.002796739,0.000746969],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9782984,0.01108951,0.00428234,0.0007413092,0.000125735,0.0003491205,0.00006848459,0.0000406008,0.00500447],"genre_scores_gemma":[0.986792,0.008797579,0.0004659957,0.00007227345,0.00008219442,0.00001844027,0.0001014429,0.00001996606,0.003650122],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02244736,"threshold_uncertainty_score":0.9999925,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01703107597853813,"score_gpt":0.3059624004654719,"score_spread":0.2889313244869337,"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."}}