{"id":"W7066384981","doi":"","title":"Individual representation and summation of symbols associated with food quantities","year":2000,"lang":"en","type":"other","venue":"Library and Archives Canada (Government of Canada)","topic":"Optical Polarization and Ellipsometry","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Representation (politics); Feature (linguistics); Algebra over a field; Class (philosophy); Pattern recognition (psychology); Noise (video)","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000003502518,0.0001240653,0.0002076941,0.00004709111,0.00002388709,0.00001315217,0.00006065254,0.00004466388,0.00006727068],"category_scores_gemma":[0.00000178993,0.0001194309,0.000009324805,0.00007753739,0.00005163791,0.0001083788,0.00001765242,0.00007531925,1.228378e-9],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000001986028,"about_ca_system_score_gemma":0.0001408548,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006279236,"about_ca_topic_score_gemma":0.01633942,"domain_scores_codex":[0.9989498,0.00002013483,0.0001592782,0.0001006194,0.0006612205,0.0001089219],"domain_scores_gemma":[0.9996781,0.00008350982,0.00008231931,0.00007996337,2.086532e-7,0.00007584364],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.0009831308,0.0003010959,0.2969598,0.01015869,0.008054177,0.0001297997,0.001654907,0.008139867,0.01278662,0.3211106,0.2883596,0.05136176],"study_design_scores_gemma":[0.005427714,0.001270592,0.5991788,0.007006595,0.0009169913,0.00001813587,0.009713297,0.02647708,0.1570805,0.002951663,0.1860074,0.00395122],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.02761023,0.0007521993,0.000105361,0.00009999943,0.0001082612,0.0001586166,0.0009672909,0.00003850827,0.9701595],"genre_scores_gemma":[0.9518343,0.0004735022,0.0002989914,0.00007209258,0.00002843096,0.000002950159,0.00009856532,0.00009319997,0.04709793],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.9242241,"threshold_uncertainty_score":0.9117782,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004562029812117441,"score_gpt":0.1400464781808403,"score_spread":0.1354844483687228,"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."}}