{"id":"W2023342744","doi":"10.1109/ccece.2010.5575231","title":"Visual sorting of recyclable goods using a support vector machine","year":2010,"lang":"en","type":"article","venue":"","topic":"Image and Object Detection Techniques","field":"Computer Science","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University; Redeemer University","funders":"","keywords":"Sorting; Support vector machine; Computer science; Artificial intelligence; Histogram; Computer vision; Scale (ratio); Rotation (mathematics); Contextual image classification; Pattern recognition (psychology); Image (mathematics); Geography; Cartography","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":[0.0004359222,0.0005352035,0.0005296672,0.0008732429,0.0002506918,0.0007018005,0.0007014006,0.0007155188,0.002753159],"category_scores_gemma":[0.001388079,0.0002308701,0.0004066758,0.0006482228,0.0002714366,0.0006812809,0.0003109681,0.0005201069,0.001106786],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003480603,"about_ca_system_score_gemma":0.0003968119,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003061364,"about_ca_topic_score_gemma":0.002245436,"domain_scores_codex":[0.9996375,0.00004791767,0.00002641067,0.0000857794,0.0001642995,0.00003804431],"domain_scores_gemma":[0.9994406,0.0001671566,0.00005227385,0.00005493398,0.0002515211,0.00003344776],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003376086,0.0001396355,0.001094088,0.00008930352,0.00004314768,0.00009080843,0.00005878693,0.02870341,0.09396119,0.0008356986,0.002418642,0.8722276],"study_design_scores_gemma":[0.00002266005,0.0002093576,0.002186997,0.00001913788,0.0000179986,0.0001119288,0.00004670758,0.9489426,0.04458709,0.001160968,0.002667754,0.000026771],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.07912485,0.0002355151,0.9124534,0.0002098719,0.0001025588,0.0001085462,0.0001360638,0.005762456,0.001866682],"genre_scores_gemma":[0.5207571,0.0002265592,0.4745601,0.0001449305,0.00004747329,0.000121433,0.0003390122,0.00006199241,0.003741348],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.003061364,"threshold_uncertainty_score":0.009210289,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01251176957968931,"score_gpt":0.293109511181964,"score_spread":0.2805977416022747,"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."}}