{"id":"W4353100172","doi":"10.54097/hset.v34i.5440","title":"Mobile Phone Price Prediction with Feature Reduction","year":2023,"lang":"en","type":"article","venue":"Highlights in Science Engineering and Technology","topic":"Spectroscopy and Chemometric Analyses","field":"Chemistry","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Dimensionality reduction; Computer science; Feature selection; Artificial intelligence; Pattern recognition (psychology); Feature (linguistics); Pearson product-moment correlation coefficient; Principal component analysis; Correlation; Mobile phone; Multilayer perceptron; Data mining; Feature extraction; Machine learning; Artificial neural network; Statistics; Mathematics","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":[0.0005605678,0.0007346176,0.0006653208,0.0009924907,0.0002407374,0.0006253545,0.0005266781,0.0004533903,0.001942771],"category_scores_gemma":[0.002495014,0.0001967697,0.001006709,0.001200499,0.000147231,0.0009045484,0.0003457015,0.0007006022,0.001027921],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003344906,"about_ca_system_score_gemma":0.000505824,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007178846,"about_ca_topic_score_gemma":0.004067284,"domain_scores_codex":[0.9994929,0.00008365852,0.00003012879,0.0001307155,0.000192305,0.00007032094],"domain_scores_gemma":[0.9994317,0.00020085,0.00005164738,0.00007980817,0.0002214451,0.00001456869],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0006397029,0.0006587845,0.02635907,0.0001790737,0.0002410758,0.000285669,0.00008066906,0.1366104,0.02093744,0.001030827,0.01004339,0.8029338],"study_design_scores_gemma":[0.0000246701,0.0002248276,0.02336979,0.0000129368,0.00006118021,0.0001207206,0.00004484983,0.959258,0.01293226,0.001201179,0.002712243,0.00003739857],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5372986,0.0009890244,0.4461086,0.0006645748,0.0003403332,0.0002502771,0.002769077,0.005058992,0.006520543],"genre_scores_gemma":[0.9086027,0.0002263638,0.08541463,0.00009548115,0.00008286564,0.0001552958,0.002680376,0.0000579254,0.002684388],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007178846,"threshold_uncertainty_score":0.01427412,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004458293926302623,"score_gpt":0.2182501920327982,"score_spread":0.2137918981064956,"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."}}