{"id":"W2101038025","doi":"10.1007/978-3-642-59742-8_35","title":"Wavelets and collocation: An interesting similarity","year":2000,"lang":"en","type":"book-chapter","venue":"International Association of Geodesy symposia","topic":"Image and Signal Denoising Methods","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Collocation (remote sensing); Similarity (geometry); Wavelet; Mathematics; Artificial intelligence; Computer science; Machine learning; Image (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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0008133062,0.0002435115,0.0003338158,0.0002551509,0.0001019139,0.0002584462,0.00077058,0.0003083163,0.0001564207],"category_scores_gemma":[0.0001559853,0.0002735771,0.0001138431,0.00005157969,0.00004305878,0.0006405748,0.0001777613,0.0003030091,0.0000278497],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003590496,"about_ca_system_score_gemma":0.0001230812,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004105949,"about_ca_topic_score_gemma":0.00002022887,"domain_scores_codex":[0.9979518,0.00009201685,0.0005690065,0.0004644653,0.0007495714,0.0001731377],"domain_scores_gemma":[0.9979137,0.0003504796,0.0007190406,0.0003151725,0.0006162131,0.00008541012],"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":[0.000057929,0.00009284516,0.000829487,0.00003786299,0.0004263416,0.00003133109,0.0008153683,0.0001377163,0.001175698,0.8552138,0.002082217,0.1390994],"study_design_scores_gemma":[0.002909797,0.000508433,0.008035624,0.001024251,0.0002032113,0.0001350041,0.00001657636,0.05828183,0.002384423,0.4336785,0.4910677,0.001754608],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.001954545,0.0003300834,0.06629447,0.004656483,0.00152104,0.0003813453,0.0001101098,0.0002302229,0.9245217],"genre_scores_gemma":[0.2064884,0.000725057,0.09985717,0.002139448,0.001183713,0.00002304963,0.0003608702,0.0001111626,0.6891111],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.4889855,"threshold_uncertainty_score":0.9999716,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0177344102691221,"score_gpt":0.2690647992918742,"score_spread":0.2513303890227521,"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."}}