{"id":"W2988401518","doi":"10.1121/1.5137277","title":"Interpreting the latent representations of a convolutional neural network trained on spectrograms","year":2019,"lang":"en","type":"article","venue":"The Journal of the Acoustical Society of America","topic":"Underwater Acoustics Research","field":"Earth and Planetary Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University","funders":"","keywords":"Spectrogram; Convolutional neural network; Computer science; Artificial intelligence; Pattern recognition (psychology); Representation (politics); Speech recognition; Machine learning","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.0006433032,0.0005619595,0.0002217506,0.0006775748,0.0001953239,0.0009389002,0.0004669126,0.0005543359,0.001492825],"category_scores_gemma":[0.002952794,0.0002179962,0.000368433,0.0004369869,0.0006399698,0.001297576,0.0006724634,0.0009847765,0.0003277996],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007102032,"about_ca_system_score_gemma":0.0004345599,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006078401,"about_ca_topic_score_gemma":0.005456254,"domain_scores_codex":[0.9997715,0.00006881014,0.00001161541,0.00005903243,0.00005294889,0.00003617104],"domain_scores_gemma":[0.9991785,0.0003304326,0.0001457101,0.0001592649,0.000152556,0.00003359722],"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":[0.0006136089,0.0001387453,0.01938036,0.0003085394,0.0001452591,0.000480541,0.0006182428,0.4394612,0.108642,0.1096586,0.006473663,0.3140792],"study_design_scores_gemma":[0.000004345234,0.00004017809,0.003612969,0.00002326898,0.00001877774,0.00005051307,0.00005799477,0.966926,0.005925328,0.02216852,0.001156097,0.00001603806],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1606024,0.0005861155,0.8332723,0.0009209125,0.0001288291,0.0000312323,0.000997426,0.0009058649,0.002554901],"genre_scores_gemma":[0.9019866,0.0004699374,0.09383247,0.0001012851,0.00007039955,0.00004145781,0.0008476712,0.0001139552,0.002536157],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006078401,"threshold_uncertainty_score":0.01208603,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01833371631018114,"score_gpt":0.2643263991220647,"score_spread":0.2459926828118835,"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."}}