{"id":"W1975399433","doi":"10.1016/j.laa.2005.08.014","title":"The geometry of linear separability in data sets","year":2005,"lang":"en","type":"article","venue":"Linear Algebra and its Applications","topic":"Advanced Statistical Methods and Models","field":"Mathematics","cited_by":8,"is_retracted":false,"has_abstract":false,"ca_institutions":"Queen's University","funders":"","keywords":"Mathematics; Geometry","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01264563,0.001225121,0.002615085,0.006390948,0.001702483,0.009944504,0.002550689,0.002139434,0.00316299],"category_scores_gemma":[0.05731962,0.00177797,0.002314841,0.005900683,0.01094862,0.01454973,0.007648146,0.005471433,0.0005817233],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002895982,"about_ca_system_score_gemma":0.001949912,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001657129,"about_ca_topic_score_gemma":0.0007642935,"domain_scores_codex":[0.9810218,0.01008846,0.001521103,0.002793995,0.004031895,0.0005428036],"domain_scores_gemma":[0.8976221,0.08031096,0.009486063,0.006460965,0.003913175,0.002206674],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0001188251,0.00003400131,0.001635271,0.0001957929,0.0001185114,0.0001508009,0.0005829002,0.01130124,0.0006721381,0.9621538,0.001257438,0.02177929],"study_design_scores_gemma":[0.00001224082,0.00002648813,0.0005644141,0.00002760462,0.00001842707,0.0001137031,0.00006727253,0.02867124,0.0002392276,0.9691812,0.001057506,0.00002066014],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05669516,0.002796863,0.9298273,0.00398441,0.0001077083,0.00006952934,0.001035766,0.0002336094,0.00524978],"genre_scores_gemma":[0.789314,0.003939558,0.1961242,0.00115395,0.001318589,0.0004586285,0.002698169,0.0002723942,0.004720424],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01264563,"threshold_uncertainty_score":0.06687731,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1337616185413844,"score_gpt":0.4536645928760404,"score_spread":0.319902974334656,"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."}}