{"id":"W6907227584","doi":"10.21227/yj3s-js83","title":"Data Fusion Contest 2016 (DFC2016)","year":2019,"lang":"en","type":"dataset","venue":"IEEE DataPort","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Panchromatic film; Multispectral image; Orthophoto; Image resolution; Sensor fusion; Image fusion; Interpolation (computer graphics); Radiometry","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0205913,0.002867651,0.003319207,0.003352007,0.003739074,0.01116374,0.004608829,0.004994309,0.05375505],"category_scores_gemma":[0.01823362,0.0007151864,0.002094652,0.003519594,0.001304537,0.006131373,0.009345312,0.00424082,0.05477627],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004184185,"about_ca_system_score_gemma":0.009177909,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0159609,"about_ca_topic_score_gemma":0.01966361,"domain_scores_codex":[0.9862627,0.002609138,0.000745008,0.001551119,0.006817804,0.0020142],"domain_scores_gemma":[0.9829109,0.001066364,0.000391534,0.002514788,0.009908627,0.003207631],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0003873837,0.0001163071,0.0002697715,0.0002198351,0.00003679985,0.00007131666,0.00005035515,0.001362246,0.001399182,0.007203102,0.9179136,0.07097015],"study_design_scores_gemma":[0.0001085973,0.0001286859,0.0007868499,0.000127064,0.00001518291,0.00009181486,0.0001102277,0.006360354,0.002271054,0.01311602,0.9768453,0.00003876006],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"methods","genre_gemma":"dataset","genre_scores_codex":[0.01736322,0.02699476,0.3158414,0.07214668,0.1022054,0.006258645,0.1301873,0.02863917,0.3003635],"genre_scores_gemma":[0.07219297,0.008364004,0.1037641,0.009854163,0.01614483,0.003055962,0.4678905,0.008786522,0.309947],"genre_candidate":"dataset","genre_consensus":null,"teacher_disagreement_score":0.05375505,"threshold_uncertainty_score":0.1798285,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1304779103304434,"score_gpt":0.3576496605661311,"score_spread":0.2271717502356878,"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."}}