{"id":"W2805615377","doi":"10.5539/jmr.v10n4p32","title":"Handwriting Detection Model Based on Four-Dimensional Vector Space Model","year":2018,"lang":"en","type":"article","venue":"Journal of Mathematics Research","topic":"Simulation and Modeling Applications","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Handwriting; Feature vector; Word (group theory); Vector space model; Sentence; Space (punctuation); Artificial intelligence; Computer science; Value (mathematics); Feature (linguistics); Pattern recognition (psychology); Natural language processing; Mathematics; Speech recognition; Machine learning; Linguistics; Geometry","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006742612,0.0007685375,0.00096087,0.001324725,0.0004296807,0.001618041,0.001653569,0.0008856934,0.002923073],"category_scores_gemma":[0.002055649,0.0003889637,0.001015504,0.001298154,0.000574821,0.00194115,0.0006193252,0.0009577807,0.001232418],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001177953,"about_ca_system_score_gemma":0.0008304308,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01551487,"about_ca_topic_score_gemma":0.00503732,"domain_scores_codex":[0.999271,0.0001230918,0.00006744396,0.0002368539,0.0002151606,0.00008652059],"domain_scores_gemma":[0.9991331,0.0002618024,0.000137966,0.00005475845,0.0003761956,0.0000363281],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001818553,0.00008765391,0.005774878,0.0001734897,0.0001256371,0.0002567525,0.0002314126,0.852657,0.004839033,0.02189944,0.002474548,0.1112983],"study_design_scores_gemma":[0.000003716089,0.00001845897,0.0003827121,0.000004182521,0.000009259951,0.00002813557,0.000007459123,0.9965779,0.0003087031,0.002271352,0.0003795872,0.000008520584],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04847632,0.001040007,0.9430262,0.0005464203,0.0001206059,0.0001056272,0.0004420747,0.001224447,0.005018378],"genre_scores_gemma":[0.9034422,0.001555825,0.07355426,0.0001373967,0.0001086653,0.0003657684,0.0008469596,0.00008204819,0.01990697],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01551487,"threshold_uncertainty_score":0.03084916,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1536204606197724,"score_gpt":0.3832515935245525,"score_spread":0.2296311329047801,"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."}}