{"id":"W3174299795","doi":"10.3390/rs13132501","title":"An Efficient Multi-Sensor Remote Sensing Image Clustering in Urban Areas via Boosted Convolutional Autoencoder (BCAE)","year":2021,"lang":"en","type":"article","venue":"Remote Sensing","topic":"Remote-Sensing Image Classification","field":"Engineering","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University; York University; Institut National de la Recherche Scientifique","funders":"University of Houston","keywords":"Autoencoder; Computer science; Artificial intelligence; Pattern recognition (psychology); Cluster analysis; Feature (linguistics); Deep learning","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":[0.0005201299,0.0007613915,0.0006322113,0.0006960857,0.0003231702,0.0004653537,0.0009240975,0.0006472712,0.0006068222],"category_scores_gemma":[0.0007913686,0.0004475274,0.0008864149,0.0007243007,0.0003450669,0.0008832041,0.0006776155,0.0007773156,0.0003524967],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005752825,"about_ca_system_score_gemma":0.0006716874,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009884979,"about_ca_topic_score_gemma":0.01124339,"domain_scores_codex":[0.9996578,0.00004083919,0.00001597036,0.0001448219,0.0000875109,0.0000531521],"domain_scores_gemma":[0.9997466,0.00005372324,0.00002809601,0.0000460773,0.0001080322,0.00001745084],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002116025,0.0001132593,0.002691869,0.0001147779,0.0001717386,0.0001410662,0.0001566024,0.5115642,0.0527575,0.002348028,0.00235339,0.427376],"study_design_scores_gemma":[0.000002936036,0.00001453433,0.0007020482,0.000003108439,0.000009695923,0.00002230799,0.000009755971,0.9923079,0.006040761,0.0005268752,0.0003524054,0.00000763498],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04883326,0.0002175233,0.9486058,0.0001073606,0.00003772997,0.00004141283,0.00009425511,0.001134259,0.0009283414],"genre_scores_gemma":[0.5345683,0.0002910099,0.460342,0.000162816,0.00003535956,0.00007073851,0.0006915719,0.0001451106,0.003693142],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.009884979,"threshold_uncertainty_score":0.01965487,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01982185856604661,"score_gpt":0.2534926158621273,"score_spread":0.2336707572960807,"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."}}