{"id":"W4386243193","doi":"10.1109/crv60082.2023.00021","title":"Learning-to-Count by Learning-to-Rank","year":2023,"lang":"en","type":"article","venue":"","topic":"Remote-Sensing Image Classification","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Computer science; Artificial intelligence; Benchmark (surveying); Ranking (information retrieval); Feature (linguistics); Pattern recognition (psychology); Pairwise comparison; Object (grammar); Annotation; Density estimation; Constraint (computer-aided design); Representation (politics); Spurious relationship; Rank (graph theory); Feature extraction; Image (mathematics); Object detection; Feature learning; Machine learning; Estimator; Mathematics; Statistics","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0002485332,0.0001695787,0.0001548079,0.0002178483,0.00009706461,0.00009772657,0.0001468995,0.00008446463,0.0001419216],"category_scores_gemma":[0.0002913412,0.0001789927,0.00004409978,0.0006987238,0.00001472874,0.00008682818,0.00004449446,0.0003187959,0.01825709],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001135479,"about_ca_system_score_gemma":0.0000102952,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002721384,"about_ca_topic_score_gemma":0.000008175792,"domain_scores_codex":[0.9988548,0.0000347874,0.000202194,0.0002752686,0.0002453416,0.0003876043],"domain_scores_gemma":[0.9994043,0.00008652937,0.00001831098,0.0002565036,0.00006176475,0.0001726529],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000006172669,0.00000815211,0.0004624741,0.00003314877,0.00002381884,0.00000867301,0.001151226,0.3742712,0.3471424,0.00002863272,0.2408326,0.03603148],"study_design_scores_gemma":[0.0001697719,0.0000830016,0.008765674,0.00002559761,0.000008858412,0.000004235306,0.00040943,0.4416892,0.01628858,0.00001783276,0.5321664,0.0003714366],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8995108,0.0000383165,0.04642215,0.002518896,0.0007077385,0.0003920829,0.000003154741,0.006987334,0.0434195],"genre_scores_gemma":[0.9566279,0.00003410599,0.001681881,0.0001475325,0.0001033493,0.00001001482,0.00004638747,0.0001032764,0.04124552],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3308538,"threshold_uncertainty_score":0.9825073,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01142944730316786,"score_gpt":0.2323007220678161,"score_spread":0.2208712747646483,"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."}}