{"id":"W3179086561","doi":"","title":"Optimal halftoning for network-based imaging","year":2001,"lang":"en","type":"article","venue":"","topic":"Hermeneutics and Narrative Identity","field":"Arts and Humanities","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"","keywords":"Computer science; Representation (politics); Artificial intelligence; Quantization (signal processing); Computer vision; Algorithm; Coherence (philosophical gambling strategy); 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":[0.0006733936,0.0004623307,0.0003796052,0.0005538577,0.000285049,0.001036593,0.000766826,0.0006199235,0.003889699],"category_scores_gemma":[0.002871464,0.0003014487,0.0003360483,0.0005206974,0.0007074903,0.001779928,0.0009886661,0.0008532538,0.0008344869],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007665082,"about_ca_system_score_gemma":0.0004501158,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001129093,"about_ca_topic_score_gemma":0.0009891641,"domain_scores_codex":[0.9997197,0.00006621455,0.00001644254,0.00005154735,0.0001242962,0.00002179973],"domain_scores_gemma":[0.9994142,0.0002776979,0.00004442979,0.0001132958,0.0001226858,0.00002763899],"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":[0.000269398,0.00005153367,0.0004158663,0.0002548843,0.00003221323,0.0001058813,0.0002728172,0.2023369,0.07126221,0.2079511,0.002383796,0.5146634],"study_design_scores_gemma":[0.00001266325,0.00003847164,0.0001226845,0.00001708959,0.000006710069,0.0001032682,0.00002944754,0.9402011,0.02158535,0.03311502,0.004750245,0.00001791136],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.004309412,0.0001296468,0.9944788,0.00005865605,0.00001606997,0.00001635891,0.0000183056,0.00009477932,0.000878001],"genre_scores_gemma":[0.125348,0.0005022991,0.8702103,0.00005617165,0.00003691982,0.00006309906,0.0001046593,0.0001535884,0.003524973],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.003889699,"threshold_uncertainty_score":0.01301235,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03437068224415264,"score_gpt":0.2537812399314875,"score_spread":0.2194105576873349,"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."}}