{"id":"W2376749417","doi":"","title":"The Research Development and Technical Framework of Functional Data Analysis","year":2012,"lang":"en","type":"article","venue":"Tongji yu xinxi luntan","topic":"Industrial Technology and Control Systems","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Functional data analysis; Data science; Multivariate analysis; Focus (optics); Computer science; Statistical analysis; Operations research; Order (exchange); Management science; Mathematics; Engineering; Statistics; Economics; Machine learning","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001925958,0.00008165134,0.0001700175,0.0001423919,0.0002180438,0.00001953769,0.00036714,0.0002518631,0.00004526288],"category_scores_gemma":[0.0001850396,0.00005952771,0.00002552488,0.0006379051,0.0001488629,0.00008954169,0.0001812159,0.0005030381,0.00002244664],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000555909,"about_ca_system_score_gemma":0.00002779781,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001631764,"about_ca_topic_score_gemma":0.00007522322,"domain_scores_codex":[0.9989682,0.00006031588,0.0002501576,0.0001353615,0.0002605296,0.0003254322],"domain_scores_gemma":[0.998861,0.0003876808,0.00002616977,0.0006255431,0.00004263749,0.00005698425],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0003576709,0.0003012537,0.2759191,0.0001479036,0.007272237,0.00001203721,0.00143829,0.001327808,0.009465415,0.4595938,0.04284305,0.2013214],"study_design_scores_gemma":[0.00122096,0.0001119449,0.329724,0.0001513491,0.0007764677,0.00007157158,0.002115627,0.01153118,0.01005193,0.004322872,0.6390076,0.0009144864],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9005158,0.01320272,0.05089461,0.001308314,0.001758725,0.0009725261,0.00006830174,0.0007742046,0.03050478],"genre_scores_gemma":[0.9987584,0.00003248673,0.0007622473,0.000004939729,0.000202513,0.00002696508,0.0000181216,0.000009584418,0.0001846845],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5961646,"threshold_uncertainty_score":0.2427469,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09552662563757866,"score_gpt":0.3253520393790301,"score_spread":0.2298254137414515,"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."}}