{"id":"W4385446408","doi":"10.3390/s23156845","title":"Analysis of Hyperspectral Data to Develop an Approach for Document Images","year":2023,"lang":"en","type":"review","venue":"Sensors","topic":"Remote-Sensing Image Classification","field":"Engineering","cited_by":29,"is_retracted":false,"has_abstract":true,"ca_institutions":"Lakehead University","funders":"","keywords":"Hyperspectral imaging; Preprocessor; Computer science; Data pre-processing; Data science; Field (mathematics); Feature extraction; Image processing; Data mining; Artificial intelligence; Information retrieval; Pattern recognition (psychology); Image (mathematics); 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001100269,0.001046783,0.0007927223,0.004191735,0.0003660647,0.002016303,0.001125137,0.00097043,0.003159112],"category_scores_gemma":[0.001326929,0.0003285348,0.0009275498,0.003584011,0.0008682547,0.002050886,0.0007023872,0.001725125,0.003009847],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006544233,"about_ca_system_score_gemma":0.0007088188,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001252184,"about_ca_topic_score_gemma":0.002067264,"domain_scores_codex":[0.9993311,0.00008791026,0.0000465305,0.0001431346,0.0003593238,0.00003195571],"domain_scores_gemma":[0.9993891,0.0001545771,0.00006364715,0.00005529977,0.0003222478,0.00001517231],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00003630296,0.00006690293,0.001345085,0.004373502,0.0001611233,0.0001812924,0.000220266,0.004281633,0.048446,0.02483262,0.01564388,0.9004115],"study_design_scores_gemma":[0.0000183419,0.0001989098,0.009518258,0.002463338,0.0003053537,0.002509018,0.0008809408,0.08083586,0.1310993,0.04848741,0.7234646,0.0002186779],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"review","genre_scores_codex":[0.007721263,0.1188414,0.8354301,0.002410186,0.001205115,0.00042872,0.001204322,0.001704139,0.03105478],"genre_scores_gemma":[0.08717895,0.1817431,0.7072127,0.001643625,0.001011294,0.000504244,0.00240789,0.0004329004,0.01786533],"genre_candidate":"review","genre_consensus":null,"teacher_disagreement_score":0.004191735,"threshold_uncertainty_score":0.01056826,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.190354951584761,"score_gpt":0.3798717034644761,"score_spread":0.1895167518797152,"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."}}