{"id":"W3112070715","doi":"","title":"Cubic and bicubic spline interpolation in Python","year":2020,"lang":"fr","type":"preprint","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Advanced Numerical Analysis Techniques","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Bicubic interpolation; Python (programming language); Computer science; Spline interpolation; Tangent; Algorithm; Mathematics; Programming language; Geometry; Computer vision; Bilinear interpolation","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":[0.00222272,0.000512113,0.0007084609,0.0003409011,0.0001316656,0.00021184,0.0007434816,0.0003983565,0.0001934275],"category_scores_gemma":[0.001260063,0.0006059512,0.0002041829,0.000963364,0.0002534573,0.0002658756,0.001183785,0.001214456,0.00007423934],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003079732,"about_ca_system_score_gemma":0.00006966692,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00188339,"about_ca_topic_score_gemma":0.002510076,"domain_scores_codex":[0.9948887,0.002497548,0.000910181,0.0009498624,0.0003212724,0.0004324544],"domain_scores_gemma":[0.9963822,0.001102148,0.000369216,0.001261728,0.0006151204,0.0002695709],"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":[0.00006010357,0.001028643,0.01861371,0.001552719,0.0003670658,0.00005273092,0.02112222,0.005778122,0.1305126,0.2731278,0.001048867,0.5467355],"study_design_scores_gemma":[0.0006996412,0.000001364005,0.01867832,0.00454312,0.0001404293,0.00001749079,0.0001690596,0.8033,0.09959316,0.04571516,0.02600104,0.001141209],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.09806637,0.003925698,0.8576584,0.02486588,0.0001711585,0.000571541,0.00004153614,0.0007086311,0.01399081],"genre_scores_gemma":[0.7319596,0.003022981,0.2623281,0.00007409469,0.00003490053,0.00007256107,0.0003065224,0.00009120631,0.002110037],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.7975219,"threshold_uncertainty_score":0.9996392,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01157191005352398,"score_gpt":0.2335000374654108,"score_spread":0.2219281274118868,"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."}}