{"id":"W3142834936","doi":"10.18280/ts.380108","title":"Comparison of Plant Leaf Classification Using Modified AlexNet and Support Vector Machine","year":2021,"lang":"en","type":"article","venue":"Traitement du signal","topic":"Smart Agriculture and AI","field":"Agricultural and Biological Sciences","cited_by":59,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Support vector machine; Artificial intelligence; Convolutional neural network; Computer science; Pattern recognition (psychology); Kernel (algebra); Classifier (UML); Plant identification; Radial basis function kernel; Transfer of learning; Identification (biology); Machine learning; Artificial neural network; Plant disease; Kernel method; Mathematics; Botany; Biology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0000932458,0.0000934322,0.0001740906,0.000006081556,0.00008817485,0.00002798033,0.00006653968,0.00004892106,0.000798656],"category_scores_gemma":[0.000004267032,0.00003600595,0.00004496978,0.0001231233,0.00002947469,0.00005828305,0.0000269496,0.00005788729,0.000002883167],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000087882,"about_ca_system_score_gemma":0.000007515094,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005359708,"about_ca_topic_score_gemma":0.0001714616,"domain_scores_codex":[0.9992392,0.00004249939,0.0002324597,0.0001842651,0.0001701123,0.0001314794],"domain_scores_gemma":[0.9997307,0.00004675001,0.00009224427,0.00002655418,0.00004717685,0.00005657567],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.00002870096,0.0001820922,0.02270406,0.00001010796,0.00001835945,0.00000351261,0.0001372973,0.00002627879,0.969939,0.0007171921,0.001269962,0.004963424],"study_design_scores_gemma":[0.0005304104,0.0004363892,0.863926,0.00003866102,0.00007585355,0.00002956509,0.001185501,0.0143464,0.1095803,0.00009893034,0.009457294,0.0002947023],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9983473,0.0001646223,0.0000367241,0.0006531156,0.00005129627,0.0001031834,0.0001281269,0.0000185864,0.0004970087],"genre_scores_gemma":[0.9990428,0.00001523642,0.0001059925,0.0000937689,0.0001543115,0.00000384612,0.0005067177,5.476433e-7,0.00007674408],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8603587,"threshold_uncertainty_score":0.8744723,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.078864074939499,"score_gpt":0.2743236516865951,"score_spread":0.1954595767470961,"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."}}