{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009488829,0.00009306048,0.0001127869,0.00101939,0.00009694332,0.00002429819,0.0001590239,0.0001280021,0.000009151808],"category_scores_gemma":[0.00004025585,0.00007384919,0.000007683177,0.005715002,0.0002243374,0.0001360338,0.00004641677,0.0001918872,0.00001897555],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007159678,"about_ca_system_score_gemma":0.00002294028,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004579032,"about_ca_topic_score_gemma":6.846554e-7,"domain_scores_codex":[0.9992043,8.396507e-7,0.00008089444,0.0003019949,0.0001463212,0.0002656771],"domain_scores_gemma":[0.9997078,0.00001196245,0.00002581492,0.0001840098,0.00003333867,0.00003706602],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.000005646472,0.0000243224,0.001524088,0.00003483945,0.00001065538,0.00001662792,0.0001563554,0.002034966,0.9916512,0.003729467,0.0002540537,0.0005577191],"study_design_scores_gemma":[0.0002449978,0.00006542412,0.00103854,0.00003632,0.00001450752,0.0001017479,0.00047366,0.006620732,0.9837156,0.0001280315,0.007411074,0.0001493652],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9976044,0.000305913,0.0001930252,0.0003587172,0.00008950268,0.0000346685,0.000003350565,0.0006505004,0.0007599751],"genre_scores_gemma":[0.9980261,0.0003417937,0.0007317169,0.000001017808,0.00004242785,0.00004213088,0.000003210107,0.000007850263,0.0008037775],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007935661,"threshold_uncertainty_score":0.3011483,"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."}}